Search results for: destination image

Authors: Fanqiang Kong, Chending Bian

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Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, simultaneous sparse representation, sparse regression, non-local means

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Andrew R. Willis, Kevin Brink, Kathleen Dipple

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This article describes a software package called ROS-georegistration intended for use with the robot operating system (ROS) and the Gazebo 3D simulation environment. ROSgeoregistration provides tools for the simulation, test, and deployment of aerial georegistration algorithms and is available at github.com/uncc-visionlab/rosgeoregistration. A model creation package is provided which downloads multi-spectral images from the Google Earth Engine database and, if necessary, incorporates these images into a single, possibly very large, reference image. Additionally a Gazebo plugin which uses the real-time sensor pose and image formation model to generate simulated imagery using the specified reference image is provided along with related plugins for UAV relevant data. The novelty of this work is threefold: (1) this is the first system to link the massive multi-spectral imaging database of Google’s Earth Engine to the Gazebo simulator, (2) this is the first example of a system that can simulate geospatially and radiometrically accurate imagery from multiple sensor views of the same terrain region, and (3) integration with other UAS tools creates a new holistic UAS simulation environment to support UAS system and subsystem development where real-world testing would generally be prohibitive. Sensed imagery and ground truth registration information is published to client applications which can receive imagery synchronously with telemetry from other payload sensors, e.g., IMU, GPS/GNSS, barometer, and windspeed sensor data. To highlight functionality, we demonstrate ROSgeoregistration for simulating Electro-Optical (EO) and Synthetic Aperture Radar (SAR) image sensors and an example use case for developing and evaluating image-based UAS position feedback, i.e., pose for image-based Guidance Navigation and Control (GNC) applications.

Keywords: EO-to-EO, EO-to-SAR, flight simulation, georegistration, image generation, robot operating system, vision-based navigation

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Authors: Joao Ferreira Do Rosario, Maria De Lurdes Calisto, Ana Teresa Machado, Nuno Gustavo, Rui Gonçalves

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The tourism sector is increasingly important to the economic performance of countries and a relevant theme to academic research, increasing the importance of understanding how and why tourists evaluate tourism locations. The city of Lisbon is currently a tourist destination of excellence in the European and world-wide panorama, registering a significant growth of the economic weight of its tourist activities in the Gross Added Value of the region. Although there is research on the feedback of those who visit tourist sites and different methodologies for studying tourist sites have been applied, this research seeks to be innovative in the objective of obtaining insights on the competitiveness in terms of attractiveness of the city of Lisbon as a tourist destination, based the feedback of tourists in the Facebook pages of the most visited museums and monuments of Lisbon, an interpretation that is relevant in the development of strategies of tourist attraction. The intangible dimension of the tourism offer, due to its unique condition of simultaneous production and consumption, makes eWOM particularly relevant. The testimony of consumers is thus a decisive factor in the decision-making and buying process in tourism. Online social networks are one of the most used platforms for tourists to evaluate the attractiveness's points of a tourism destination (e.g. cultural and historical heritage), with this user-generated feedback enabling relevant information about the customer-tourists. This information is related to the tourist experience representing the true voice of the customer. Furthermore, this voice perceived by others as genuine, opposite to marketing messages, may have a powerful word-of-mouth influence on other potential tourists. The relevance of online reviews sharing, however, becomes particularly complex, considering social media users’ different profiles or the possible and different sources of information available, as well as their associated reputation associated with each source. In the light of these trends, our research focuses on the tourists’ feedback on Facebook pages of the most visited museums and monuments of Lisbon that contribute to its attractiveness as a tourism destination. Sentiment Analysis is the methodology selected for this research, using public available information in the online context, which was deemed as an appropriate non-participatory observation method. Data will be collected from two museums (Museu dos Coches and Museu de Arte Antiga) and three monuments ((Mosteiro dos Jerónimos, Torre de Belém and Panteão Nacional) Facebook pages during a period of one year. The research results will help in the evaluation of the considered places by the tourists, their contribution to the city attractiveness and present insights helpful for the management decisions regarding this museums and monuments. The results of this study will also contribute to a better knowledge of the tourism sector, namely the identification of attributes in the evaluation and choice of the city of Lisbon as a tourist destination. Further research will evaluate the Lisbon attraction points for tourists in different categories beyond museums and monuments, will also evaluate the tourist feedback from other sources like TripAdvisor and apply the same methodology in other cities and country regions.

Keywords: Lisbon tourism, opinion mining, sentiment analysis, tourism location attractiveness evaluation

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Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: construction, coordinate, engineering, GIS, management, map

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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

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Authors: Phillip F. Kanokanga, Patrick W. Mamimine, Molline Mwando, Charity Mapingure

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Tourism development tends to follow anchor attractions, including cities and their surroundings, while marginalizing small towns and their environs. This is even though the small towns and their hinterlands can also offer competitive tourism products. The Zimbabwe Tourism Authority (ZTA) gathers visitor statistics of major tourist destinations only thereby sidelining the density of tourist traffic that either passes through or visits the small towns in the country. Unless this problem is addressed, the tourism potential of small towns and their hinterlands will not be fully tapped for economic development. Using qualitative research methodology, this study investigated the opportunities for tourism development in the Greater Chinhoyi Area. The study revealed that the Greater Chinhoyi area had potential for heritage tourism, village tourism, urban tourism, educational tourism, dark tourism, recreational tourism, agrotourism, and nature tourism. There is a need to link the various tourism resources in the Greater Chinhoyi area to anchor attractions in dominant resorts, then develop and present the tourism products in transit towns as ‘appetisers’ or ‘appetisser attractions’ before one gets to the main destination.

Keywords: anchor attractions, appetisers, heritage tourism, agrotourism, small towns, tourism corridor, systems approach, hidden treasures

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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

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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

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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: 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: 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

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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: 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: 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: Shuyu Zhao

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This study uses the cat-themed "Night at the Museum" event of the Shanghai Museum as a case to examine how museum events are portrayed across various digital news platforms. Grounded in communication and cultural creativity theories and employing a three-tier framing approach, this research provides an in-depth analysis of media strategies in cross-platform museum image building. Through a quantitative content analysis, it is investigated that how digital media employ specific narrative strategies to shape the public perception of museum events. The findings reveal a prevalent use of leadership framing, highlighting the museum's unique role in cultural dissemination. By combining elements of museum culture with a pet-friendly theme, the "catty Night at the Museum" event serves as a distinctive example in exploring museum image construction within digital media. This study sheds light on how museum events, as unique cultural arenas, are positioned in the public mind, offering a fresh perspective for the promotion and image-building of museum activities.

Keywords: cultural communication, digital media, museum, framing theory

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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

Abstract:

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: Jayron Sanchez, Analyn Yumang, Felicito Caluyo

Abstract:

The visually impaired individual may use a cane, guide dog or ask for assistance from a person. This study implemented the RFID technology which consists of a low-cost RFID reader and passive RFID tag cards. The passive RFID tag cards served as checkpoints for the visually impaired. The visually impaired was guided through audio output from the system while traversing the path. The study implemented an ultrasonic sensor in detecting static obstacles. The system generated an alternate path based on A* algorithm to avoid the obstacles. Alternate paths were also generated in case the visually impaired traversed outside the intended path to the destination. A* algorithm generated the shortest path to the destination by calculating the total cost of movement. The algorithm then selected the smallest movement cost as a successor to the current tag card. Several trials were conducted to determine the effect of obstacles in the time traversal of the visually impaired. A dependent sample t-test was applied for the statistical analysis of the study. Based on the analysis, the obstacles along the path generated delays while requesting for the alternate path because of the delay in transmission from the laptop to the device via ZigBee modules.

Keywords: A* algorithm, RFID technology, ultrasonic sensor, ZigBee module

Procedia PDF Downloads 409

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

Procedia PDF Downloads 251

Authors: Scott Wysong

Abstract:

Qatar will spend billions of dollars to host the 2022 World Cup. While football fans around the globe get excited to cheer on their favorite team every four years, critics debate the merits of a country hosting such an expensive and large-scale event. That is, the host countries spend billions of dollars on stadiums and infrastructure to attract these mega sporting events with the hope of equitable returns in economic impact and creating jobs. Yet, in many cases, the host countries are left in debt with decaying venues. There are benefits beyond the economic impact of hosting mega-events. For example, citizens are often proud of their city/country to host these famous events. Yet, often overlooked in the literature is the proposition that serving as the host for a mega-event may enhance the country’s brand image, not only as a tourist destination but for the products made in that country of origin. This research aims to explore this phenomenon by taking an exploratory look at consumer perceptions of three host countries of a mega-event in sports. In 2014, the U.S., Chinese and Finn (Finland) consumer attitudes toward Brazil and its products were measured before and after the World Cup via surveys (n=89). An Analysis of Variance (ANOVA) revealed that there were no statistically significant differences in the pre-and post-World Cup perceptions of Brazil’s brand personality or country-of-origin image. After the World Cup in 2018, qualitative interviews were held with U.S. sports fans (n=17) in an effort to further explore consumer perceptions of products made in the host country: Russia. A consistent theme of distrust and corruption with Russian products emerged despite their hosting of this prestigious global event. In late 2021, U.S. football (soccer) fans (n=42) and non-fans (n=37) were surveyed about the upcoming 2022 World Cup. A regression analysis revealed that how much an individual indicated that they were a soccer fan did not significantly influence their desire to visit Qatar or try products from Qatar in the future even though the country was hosting the World Cup—in the end, hosting a mega-event as grand as the World Cup showcases the country to the world. However, it seems to have little impact on consumer perceptions of the country, as a whole, or its brands. That is, the World Cup appeared to enhance already pre-existing stereotypes about Brazil (e.g., beaches, partying and fun, yet with crime and poverty), Russia (e.g., cold weather, vodka and business corruption) and Qatar (desert and oil). Moreover, across all three countries, respondents could rarely name a brand from the host country. Because mega-events cost a lot of time and money, countries need to do more to market their country and its brands when hosting. In addition, these countries would be wise to measure the impact of the event from different perspectives. Hence, we put forth a comprehensive future research agenda to further the understanding of how countries, and their brands, can benefit from hosting a mega sporting event.

Keywords: branding, country-of-origin effects, mega sporting events, return on investment

Procedia PDF Downloads 281