Search results for: landscape image

Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Mads Dyrmann, Robert Poulsen

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For the past three years, the Danish project, RoboWeedSupport, has sought to bridge the gap between the potential herbicide savings using a decision support system and the required weed inspections. In order to automate the weed inspections it is desired to generate a map of the weed species present within the field, to generate the map images must be captured with samples covering the field. This paper investigates the economical cost of performing this data collection based on a camera system mounted on a all-terain vehicle (ATV) able to drive and collect data at up to 50 km/h while still maintaining a image quality sufficient for identifying newly emerged grass weeds. The economical estimates are based on approximately 100 hectares recorded at three different locations in Denmark. With an average image density of 99 images per hectare the ATV had an capacity of 28 ha per hour, which is estimated to cost 6.6 EUR/ha. Alternatively relying on a boom solution for an existing tracktor it was estimated that a cost of 2.4 EUR/ha is obtainable under equal conditions.

Keywords: weed mapping, integrated weed management, weed recognition, image acquisition

Procedia PDF Downloads 219

Authors: Agustinus Rudatyo Himamunanto, Anastasia Rita Widiarti

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Transliteration using Javanese manuscripts is one of methods to preserve and legate the wealth of literature in the past for the present generation in Indonesia. The transliteration manual process commonly requires philologists and takes a relatively long time. The automatic transliteration process is expected to shorten the time so as to help the works of philologists. The preprocessing and segmentation stage firstly done is used to manage the document images, thus obtaining image script units that will compile input document images free from noise and have the similarity in properties in the thickness, size, and slope. The next stage of characteristic extraction is used to find unique characteristics that will distinguish each Javanese script image. One of characteristics that is used in this research is the number of black pixels in each image units. Each image of Java scripts contained in the data training will undergo the same process similar to the input characters. The system testing was performed with the data of the book Hamong Tani. The book Hamong Tani was selected due to its content, age and number of pages. Those were considered sufficient as a model experimental input. Based on the results of random page automatic transliteration process testing, it was determined that the maximum percentage correctness obtained was 81.53%. The percentage of success was obtained in 32x32 pixel input image size with the 5x5 image window. With regard to the results, it can be concluded that the automatic transliteration model offered is relatively good.

Keywords: Javanese script, character recognition, statistical, automatic transliteration

Procedia PDF Downloads 330

Authors: Marek Maruszczak

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Gamified applications have been used successfully in education for years. The rapid development of technologies such as augmented reality and image recognition increases their availability and reduces their prices. Thus, there is an increasing possibility and need for a wide use of such applications in education. The main purpose of this article is to present the effects of work on a mobile application with augmented reality, the aim of which is to motivate tourists to pay more attention to the attractions and increase the likelihood of moving from one attraction to the next while visiting the Palácio Nacional de Sintra in Portugal. Work on the application was carried out together with the employees of Parques de Sintra from 2019 to 2021. Their effect was the preparation of a mobile application using augmented reality and image recognition. The application was tested on the palace premises by both Parques de Sintra employees and tourists visiting Palácio Nacional de Sintra. The collected conclusions allowed for the formulation of good practices and guidelines that can be used when designing gamified apps for the purpose of cultural education.

Keywords: augmented reality, cultural education, gamification, image recognition, mobile games

Procedia PDF Downloads 180

Authors: Fathi Kallel, Saida Khachira, Mohamed Ben Slima, Ahmed Ben Hamida

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Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures.

Keywords: medical image processing, ultrasound images, Speckle noise, image enhancement, speckle filtering, segmentation, snakes

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Chevonne Reynolds, Robert J. Fletcher, Jr, Celine M. Carneiro, Nicole Jennings, Alison Ke, Michael C. LaScaleia, Mbhekeni B. Lukhele, Mnqobi L. Mamba, Muzi D. Sibiya, James D. Austin, Cebisile N. Magagula, Themba’alilahlwa Mahlaba, Ara Monadjem, Samantha M. Wisely, Robert A. McCleery

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A key challenge for the developing world is reconciling biodiversity conservation with the growing demand for food. In these regions, agriculture is typically interspersed among other land-uses creating heterogeneous landscapes. A primary hypothesis for promoting biodiversity in agricultural landscapes is the habitat heterogeneity hypothesis. While there is evidence that landscape heterogeneity positively influences biodiversity, the application of this hypothesis is hindered by a need to determine which components of landscape heterogeneity drive these effects and at what spatial scale(s). Additionally, whether diverse taxonomic groups are similarly affected is central for determining the applicability of this hypothesis as a general conservation strategy in agricultural mosaics. Two major components of landscape heterogeneity are compositional and configurational heterogeneity. Disentangling the roles of each component is important for biodiversity conservation because each represents different mechanisms underpinning variation in biodiversity. We identified a priori independent gradients of compositional and configurational landscape heterogeneity within an extensive agricultural mosaic in north-eastern Swaziland. We then tested how bird, dung beetle, ant and meso-carnivore diversity responded to compositional and configurational heterogeneity across six different spatial scales. To determine if a general trend could be observed across multiple taxa, we also tested which component and spatial scale was most influential across all taxonomic groups combined, Compositional, not configurational, heterogeneity explained diversity in each taxonomic group, with the exception of meso-carnivores. Bird and ant diversity was positively correlated with compositional heterogeneity at fine spatial scales < 1000 m, whilst dung beetle diversity was negatively correlated to compositional heterogeneity at broader spatial scales > 1500 m. Importantly, because of these contrasting effects across taxa, there was no effect of either component of heterogeneity on the combined taxonomic diversity at any spatial scale. The contrasting responses across taxonomic groups exemplify the difficulty in implementing effective conservation strategies that meet the requirements of diverse taxa. To promote diverse communities across a range of taxa, conservation strategies must be multi-scaled and may involve different strategies at varying scales to offset the contrasting influences of compositional heterogeneity. A diversity of strategies are likely key to conserving biodiversity in agricultural mosaics, and we have demonstrated that a landscape management strategy that only manages for heterogeneity at one particular scale will likely fall short of management objectives.

Keywords: agriculture, biodiversity, composition, configuration, heterogeneity

Procedia PDF Downloads 250

Authors: Esengül Elibol, Arzu Kader Harmancı Seren

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Individuals' reasons to choose a profession, profession image perceptions and future plans related to that profession affect their success in their future work lives. For nursing profession, this situation at the same time is important in terms of the health and safety of patients. The purpose of this study is to determine why medical vocational high school students in İstanbul choose nursing profession, their nursing image perceptions and future plans related to the profession. Descriptive and cross-sectional design are used. The study was carried out in four medical vocational high school in İstanbul. All third and fourth grade students who are attending to nursing programs and voluntary for participation were included in the study. In collecting data, two questionnaires that aim to learn about socio-demographic characteristics, profession choice reasons and future plans of nursing students and ‘Nursing Image Scale’ were used. Scale consisted of 28 items including individuals' opinions on nursing profession image and three sub-categories ‘General View,’ ‘Communication,’ and ‘Vocational-Educational Qualities.’ Analyzing profession choice reasons and future plans of participants, it is determined that majority chose nursing for easily finding a job (46.9%) and that majority had a dream profession other than nursing (65.8%). Analyzing nursing image perception of participants, it is determined that average of general view sub-category total scores was 9.75±2.27, average of communication sub-category total scores was8.68±2.86, and average of vocational-educational qualities sub-category total score was 21.18±3.96. In the perception score averages, meaningful differences were found according to independent variables. In conclusion, it was determined that majority of the participant students chose nursing for easily finding a job, perceived profession image negatively, and had a dream profession other than nursing.

Keywords: nursing image, medical vocational health school, perception, profession, student nurse

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Authors: Navdeep Goel, Salvador Gabarda

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Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4x4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4*4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4*4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: chirp signals, image multiplexing, image transformation, linear canonical transform, polynomial approximation

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Authors: Sarah Marie

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In today's dynamic financial landscape, cryptocurrencies represent a paradigm shift characterized by innovation and intense debate. This study probes into their transformative potential and the challenges they present, offering a balanced perspective that recognizes both their promise and pitfalls. Emulating the engaging style of a TED Talk, this research goes beyond academic analysis, serving as a critical bridge to reconcile the perspectives of cryptocurrency skeptics and enthusiasts, fostering a well-informed dialogue. The study employs a mixed-method approach, analyzing current trends, regulatory landscapes, and public perceptions in the cryptocurrency domain. It distinguishes genuine innovators in this field from ostentatious opportunists, echoing the sentiment that real innovation should be separated from mere showmanship. If one is unfamiliar with who is being referenced, they can likely spot them leaning against their Lamborghinis outside "Crypto" conventions, looking greasy. Major findings reveal a complex scenario dominated by regulatory uncertainties, market volatility, and security issues, emphasizing the need for a coherent regulatory framework that balances innovation with risk management and sustainable practices. The study underscores the importance of transparency and consumer protection in fostering responsible growth within the cryptocurrency ecosystem. In conclusion, the research advocates for education, innovation, and ethical governance in the realm of cryptocurrencies. It calls for collaborative efforts to navigate the intricacies of this evolving landscape and to realize its full potential in a responsible, inclusive, and forward-thinking manner.

Keywords: financial landscape, innovation, public perception, transparency

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Authors: Jorge Luis Morales Romero, Enrique Murillo Othón

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Business to business (B2B) relationships generally go beyond a purely profit-based result, with firms seeking to maintain a relationship for many years because a breakup or getting a new supplier can be very costly. Therefore, identifying the factors which determine a successful relationship in the long term is of great interest to companies. That is why their reputation and the brand image that customers have of them are among the main factors that can achieve a successful relationship; Because of the positive effect which is driven by the client’s loyalty. Additionally, the perception that a customer may have about a brand is different when it is related to goods or to services. Thereby, they create in their minds their own brand image of it based on the past experiences they have had; Thus, a positive relationship is established between goods-related brand image, service-related brand image, and customer loyalty. The present investigation examines the boundary conditions of said relationship by testing the moderating effects of trust, commitment, and relationship value in a B2B environment. All the variables were tested independently as moderators for service-related brand image/loyalty and for goods-related brand image/loyalty, as they are assumed to be separate variables. Survey data was collected through interviews with customers that have both a product-buying relationship and a service relationship with a global B2B brand of healthcare equipment operating in the Mexican healthcare market. Interviewed respondents were either the user or the purchasing manager and/or the responsible for the equipment maintenance for the customer organization. Hence, they were appropriate informants regarding the B2B relationship with this healthcare brand. The moderation models were estimated using the PROCESS macro for the Statistical Package for the Social Sciences Software (SPSS). Results show statistical evidence that both Relationship Value and Trust are significant moderators for the service-related brand image/loyalty relation but not significant for the goods-related brand/loyalty relation. On the other hand, Commitment results in a significant moderator for the goods-related brand/loyalty relation but is not significant for the service-related brand image/loyalty relation.

Keywords: commitment, trust, relationship value, loyalty, B2B, moderator

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Authors: Pratik Gandhi, Kavitha Chandra, Charles Thompson

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A computational model of the acoustic room impulse response between transmitters and receivers located in an enclosed cavity under the influence of frequency-dependent reflection coefficients of the walls is presented. The characteristic features of the impulse responses that differentiate these results from frequency-independent reflecting surfaces are discussed. The image-source model is derived from the first principle solution to Green's function of the acoustic wave equation. The post-processing of the computed impulse response with a band-pass filter to better represents the response of a loud-speaker is demonstrated.

Keywords: acoustic room impulse response, frequency dependent reflection coefficients, Green's function, image model

Procedia PDF Downloads 217

Authors: Mohan Bilikallahalli Sannathimmappa, Vinod Nambiar, Rajeev Aravindakshan

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Background: Image-based teaching-learning module is innovative student-centered andragogy. The objective of our study was to explore medical students’ perception of effectiveness of image-based learning strategy in promoting their lifelong learning skills and evaluate its impact on improving students’ exam grades. Methods: A prospective single-cohort study was conducted on undergraduate medical students of the academic year 2021-22. The image-based teaching-learning module was assessed through pretest, posttest, and exam grades. Students’ feedback was collected through a predesigned questionnaire on a 3-point Likert Scale. The reliability of the questionnaire was assessed using Cronbach’s alpha coefficient test. In-Course Exam-4 results were compared with In-Course Exams 1, 2, and 3. Correlation coefficients were worked out wherever relevant to find the impact of the exercise on grades. Data were collected, entered into Microsoft Excel, and statistically analyzed using SPSS version 22. Results: In total, 127 students were included in the study. The posttest scores of the students were significantly high (24.75±) as compared to pretest scores (8.25±). Students’ opinion towards the effectiveness of image-based learning in promoting their lifelong learning skills was overwhelmingly positive (Cronbach’s alpha for all items was 0.756). More than 80% of the students indicated image-based learning was interesting, encouraged peer discussion, and helped them to identify, explore, and revise key information and knowledge improvement. Nearly 70% expressed image-based learning enhanced their critical thinking and problem-solving skills. Nine out of ten students recommended image-based learning module for future topics. Conclusion: Overall, Image-based learning was found to be effective in achieving undergraduate medical students learning outcomes. The results of the study are in favor of the implementation of Image-based learning in Microbiology courses. However, multicentric studies are required to authenticate our study findings.

Keywords: active learning, knowledge, medical education, microbes, problem solving

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Authors: Tian Xia, Yuan Yan Tang

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In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

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Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

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Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Suangsuda Subjaroen, Chutikarn Sriviboon, Rosjana Chandhasa

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This research aims to examine the graduates' overall satisfaction and influential factors that affect the image of Suan Sunandha Rajabhat University, according to the graduates' viewpoints on the graduation rehearsal day. In accordance with the graduates' perceptions, the study is related to the levels of graduates' satisfaction, their perceived quality, perceived value, and the image of Suan Sunandha Rajabhat University. The sample group in this study involved 1,129 graduates of Suan Sunandha Rajabhat University who attended on 2019 graduation rehearsal day. A questionnaire was used as an instrument in order to collect data. By the use of computing software, the statistics used for data analysis were various, ranging from frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and Multiple Regression Analysis. The majority of participants were graduates with a bachelor's degree, followed by masters graduates and PhD graduates, respectively. Among the participants, most of them graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. Overall, the graduates were satisfied with the graduation rehearsal day, and each aspect was rated at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation rehearsal personnel and staff, venue, and facilities. Referring to graduates' perceptions, the perceived quality was rated at a very good level, the perceived value was at a good level, whereas the image of Suan Sunandha Rajabhat University was perceived at a good level, respectively. There were differences in satisfaction levels among graduates with a bachelor's degree, graduates with a master's degree and a doctoral degree with statistical significance at the level of 0.05. There was a statistical significance at the level of 0.05 in perceived quality and perceived value affecting the image of Suan Sunandha Rajabhat University. The image of Suan Sunandha Rajabhat University influenced graduates' satisfaction level with statistical significance at the level of 0.01.

Keywords: university image, perceived quality, perceived value, intention to study higher education, intention to recommend the university to others

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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Authors: Karolina Porada

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Over the last 40 years, there has been a trend in landscape architecture which supporters do not perceive the role of pro-ecological or postmodern solutions in the design of public green spaces as an essential goal, shifting their attention to the 'sculptural' shaping of areas with the use of slopes, hills, embankments, and other forms of terrain. This group of designers can be considered avant-garde, which in its activities refers to land art. Initial research shows that such applications are particularly frequent in places of former post-industrial sites and landfills, utilizing materials such as debris and post-mining waste in their construction. Due to the high degradation of the environment surrounding modern man, the brownfields are a challenge and a field of interest for the representatives of landscape architecture avant-garde, who through their projects try to recover lost lands by means of transformations supported by engineering and ecological knowledge to create places where nature can develop again. The analysis of a dozen or so facilities made it possible to come up with an important conclusion: apart from the cultural aspects (including artistic activities), the green areas formally referring to the land are important in the process of remediation of post-industrial sites and waste recycling (e. g. from construction sites). In these processes, there is also a potential for applying the concept of Natural Based Solutions, i.e. solutions allowing for the natural development of the site in such a way as to use it to cope with environmental problems, such as e.g.  air pollution, soil phytoremediation and climate change. The paper presents examples of modern parks, whose compositions are based on shaping the surface of the terrain in a way referring to the land art, at the same time providing an example of brownfields reuse and application of waste recycling.  For the purposes of object analysis, research methods such as historical-interpretation studies, case studies, qualitative research or the method of logical argumentation were used. The obtained results provide information about the role that landscape architecture can have in the process of remediation of degraded areas, at the same time guaranteeing the benefits, such as the shaping of landscapes attractive in terms of visual appearance, low costs of implementation, and improvement of the natural environment quality.

Keywords: brownfields, contemporary parks, landscape architecture, remediation

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Authors: R. Jannat, N. S. Juyena, F. Y. Bari, M. N. Islam

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Understanding anatomy of female reproductive organs is very much important to identify any variation in disease condition. Therefore, this study was conducted to determine the morphometry of female reproductive tract in small ruminant using ultrasonography. The reproductive tracts of 2l does and 20 ewes were collected, and both gross and ultrasonographic image measurements were performed to study morphometry of cervix, body of uterus, horn of uterus and ovary. Water bath ultrasonography technique was used with trans-abdominal linear probe for image measurements. Results revealed significant (P<0.001) variation among gross and image measurements of cervix, body of uterus and ovaries in does whereas, significant (P<0.001) variation existed between gross and image measurements of ovaries diameter in ewes. Gross measurements were proportionately higher than image measurements in both species. The mean length and width were found higher in right ovaries than those of left ovaries. In addition, the diameter of right ovaries was higher than those of left ovaries in both species. Pearson's correlation revealed a positive relation between two measurements. Moreover, it was found that echogenicity varied with reproductive organs. This is a model study. This study may help to identify female reproductive structures by trans-abdominal ultrasonography.

Keywords: female reproductive tract, morphometry, small ruminants, ultrasonography

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Authors: Rolando Volzone

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The Congregation of Saint Paul of Serra de Ossa (Ossa Mountain) was founded in 1482, originated by the eremitic movement of the homens da pobre vida (poor life men), which is documented since 1366. The community of hermits expanded up to the first half of the 15th century, mostly in southern Portugal in the Alentejo region. In 1578, following a process of institutionalization led by the Church, an autonomous congregation was set up, affiliated in the Hungarian Order of Saint Paul the First Hermit, until 1834, when the decree of dissolution of the religious orders disbanded all the convents and monasteries in Portugal. The architectural evidences that reached our days as a legacy of the hermitical movement in Serra de Ossa, although studied and analysed from an historical point of view, are still little known with respect to the architectural characteristics of its physical implantation and its relationship with the natural systems. This research intends to expose the appropriation process of the locus eremus as a starting point for the interpretation of this landscape, evidencing the close relationship between the religious experience and the physical space chosen to reach the perfection of the soul. The locus eremus is thus determined not only by practical aspects such as the absolute and relative location, orography, existence of water resources, or the King’s favoring to the religious and settlement action of the hermits, but also by spiritual aspects related to the symbolism of the physical elements present and the solitary walk of these men. These aspects, combined with the built architectural elements and other exerted human action, may be fertile ground for the definition of a hypothetical hermitical landscape based on the sufficiently distinctive characteristics that sustain it. The landscape built by these hermits is established as a cultural and material heritage, and its preservation is of utmost importance. They deeply understood this place and took advantage of its natural resources, manipulating them in an ecological and economically sustainable way, respecting the place, without overcoming its own genius loci but becoming part of it.

Keywords: architecture, congregation of Saint Paul of Serra de Ossa, heremitical landscape, locus eremus

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Authors: Sangeeta Yadav, Mantosh Biswas

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In this paper, we proposed an improved color based K-mean algorithm for clustering of satellite Image (SAR). Our method comprises of two stages. The first step is an interactive selection process where users are required to input the number of colors (ncolor), number of clusters, and then they are prompted to select the points in each color cluster. In the second step these points are given as input to K-mean clustering algorithm that clusters the image based on color and Minimum Square Euclidean distance. The proposed method reduces the mixed pixel problem to a great extent.

Keywords: cluster, ncolor method, K-mean method, interactive selection process

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Authors: Irene Yi

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This paper analyzes the development of Kurdish language endangerment in Turkey and Kurdish language education over time. It examines the historical context of the Turkish state, as well as reasons for the Turkish language hegemony. From a linguistic standpoint, the Kurdish language is in danger of extinction despite a large number of speakers, lest Kurdish language education is more widely promoted. The paper argues that Kurdish is no longer in a stable diglossic state; if the current trends continue, the language will lose its vitality. This paper recognizes the importance of education in preserving the language while discussing the changing political and institutional regard for Kurdish education. Lastly, the paper outlines solutions to the issue by looking at a variety of proposals, from creating a Kurdistan to merely changing the linguistic landscape in Turkey. After analysis of possible solutions in terms of realistic ability and effectiveness, the paper concludes that changing linguistic landscape and increasing Kurdish language education are the most ideal first steps in a long fight for Kurdish linguistic equality.

Keywords: endangered, Kurdish, oppression, policy

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

Abstract:

In this paper, we propose a new encryption system for security issues meteorological images from Meteosat Second Generation (MSG), which generates 12 images every 15 minutes. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every 15 minutes that will be used to encrypt each frame of the MSG meteorological basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, satellite MSG, encryption, decryption, key, correlation

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

Abstract:

In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes

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Authors: R. Sumalatha, M. V. Subramanyam

Abstract:

In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR.

Keywords: salt and pepper noise, ASMF, PSNR, MSE

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Authors: William Huang

Abstract:

Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Jonas Volungevicius, Kristina Amaleviciute, Rimantas Vaisvalavicius, Alvyra Slepetiene, Darijus Veteikis

Abstract:

Lithuanian territory is characterized by landscape with prevailing morain hills and clayey lowlands. The largest part of it has endured agrogenization of various degrees which was the cause of changes both in the structure of landscape and soil cover, transformations of soil profile and degradation of natural background soils. These changes influence negatively geoecological potential of landscape and soil and contribute to the weakening of the sustainability of agroecosystems. Research objective: to reveal the landscape agrogenization induced alterations of catenae and their appendant soil profiles in Lithuanian morain hills and clayey lowlands. Methods: Soil cover analysis and catenae charting was conducted using landscape profiling; soil morphology detected and soil type identified following WRB 2014. Granulometric composition of soil profiles was obtained by laser diffraction method (lazer diffractometer Mastersizer 2000). pH was measured in H2O extraction using potentiometric titration; SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. Results: analysis showed that the decrease of forest vegetation and the other natural landscape components following the agrogenization of the research area influenced differently but significantly the structural alterations in soil cover and vertical soil profile. The research detected that due to landscape agrogenization, the suppression of zone-specific processes and the intensification of inter-zone processes determined by agrogenic factors take place in Lithuanian agroecosystems. In forested hills historically prevailing Retisols and Histosols territorial complex is transforming into the territorial complex of Regosols, Deluvial soils and drained Histosols. Processes taking place are simplification of vertical profile structure, intensive rejuvenation of profile, disappearance of the features of zone-specific soil-forming processes (podzolization, lessivage, gley formation). Erosion and deluvial processes manifest more intensively and weakly accumulating organic material more intensively spread in a vertical soil profile. The territorial soil complex of Gleyic Luvisols and Gleysols dominating in forested clayey lowlands subjected to agrogenization is transformed into the catena of drained Luvisols and pseudo Cambisols. The best expressed are their changes in moisture regime (morphological features of gley and stagnic properties are on decline) together with alterations of pH and distribution and intensity of accumulation of organic matter in profile. A specific horizon, antraquic, uncharacteristic to natural soil formation is appearing. Important to note that due to deep ploughing and other agrotechnical measures, the natural vertical differentiation of clay particles in a soil profile is destroyed which leads not only to alterations of physical qualities of soil, but also encumbers the identification of Luvisols by creating presumptions to misidentify them as Cambisols. The latter have never developed in these ecosystems under the present climatic conditions. Acknowledgements: This work was supported by the National Science Program: The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agroecosystems, landscape agrogenization, luvisols, retisols, transformation of soil profile

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Authors: Innocent Pangapanga, Eric Mungatana

Abstract:

Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

Procedia PDF Downloads 103