Search results for: high quality image

Authors: Yi Shan Wu, Ting Hsuan Wu, Li Wei Cheng, Pei Yu Guo

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Given the fiercely competitive environment, human capital is one of the most valuable assets in a commercial enterprise. Therefore, developing strategies to acquire more talents is crucial. Talents are mainly attracted by both internal and external employer brands as well as by the messages conveyed from the employer image. This not only manifests the importance of a brand and an image of an organization but shows people might be affected by their personal values when assessing an organization as an employer. The goal of the present study is to examine the association between employer brand, employer image, and the likelihood of increasing organizational attractiveness. In addition, we draw from social identity theory to propose value congruence may affect the relationship between employer brand and employer image. Data was collected from those people who only worked less than a year in the industry via an online survey (N=209). The results show that employer image partly mediates the effect of employer brand on organizational attractiveness. In addition, the results also suggest that value congruence does not moderate the relationship between employer brand and employer image. These findings explain why building a good employer brand could enhance organization attractiveness and indicate there should be other factors that may affect employer image building, offering directions for future research.

Keywords: organizational attractiveness, employer brand, employer image, value congruence

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Authors: Vahid Bairami Rad

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With the rapid growth of the Internet and the globalization of the market, most enterprises are trying to attract and win customers in the highly competitive electronic market. Better e-service quality will enhance the relationship with customers and their satisfaction. So the measurement of eservice quality is very important but it is a complex process due to the complex nature of services. Literature predicts that there is a lack of universal definition of e-service quality. The e-service quality measures in banking have great importance in achieving high customer base. This paper proposes a conceptual model for measuring e-service quality in Iranian Banking Iran. Nine dimensions reliability, ease of use, personalization, security and trust, website aesthetic, responsiveness, contact and speed of delivery had been identified. The results of this paper may help to develop a proper scale to measure the e-service quality in Iranian Banking Industry, which may assist to maintain and improve the performance and effectiveness of e-service quality to retain customers.

Keywords: electronic banking, Dimensions, customer service quality, electronic, communication

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Authors: Ahmed A. Al-Mudhafar, Ali A. Abduljabar, Hayder Jawad Albattat

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This work suggests a new microwave resonator sensor (MRS) device for measuring the oil’s breakdown voltage of high voltage transformers. A precise high-sensitivity sensor is designed and manufactured based on a microstrip split ring resonator (SRR). To improve the sensor sensitivity, a RF amplifier of 30 dB gain is linked through a transmission line of 50Ω.The sensor operates at a microwave band (L) with a quality factor of 1.35x105 when it is loaded with an empty tube. In this work, the sensor has been tested with three samples of high voltage transformer oil of different ages (new, middle, and damaged) where the quality factor differs with each sample. A mathematical model was built to calculate the breakdown voltage of the transformer oils and the accuracy of the results was higher than 90%.

Keywords: active resonator sensor, oil breakdown voltage, transformers oils, quality factor

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Authors: Abigail Qian Zhou

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In recent years, the prosperity of mass tourism in China has accelerated the breadth and depth of direct communication between countries, and the national image has been placed in a new communication context. Outbound tourists are not only directly involved in the formation of the national image, but are also the most direct medium and the most active symbol representing the national image. This study uses Chinese middle-class tourists visiting Japan as a case study, and analyzes, through participant observation and semi-structured interviews, the communication function of the national image transmitted by 'human medium' in tourism activities. It also explores the 'human medium' in the era of mass tourism. This study hopes to build a bridge for tourism research and national image and media studies. It will provide a theoretical basis and practical guidance for promoting the national image, strengthening exchanges between tourists and local populations, and expanding the tourism market in the future.

Keywords: human medium, national image, communication, Chinese middle class, outbound tourists

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Authors: Christian Röling, Elena Y. Poimanova, Vladimir V. Bruevich

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Here we demonstrate a non-destructive optical technique to localize and characterize single crystals of semiconductive organic materials – Spectroscopic Imaging Ellipsometry. With a combination of microscopy and ellipsometry, it is possible to characterize even micro-sized thin film crystals on plane surface regarding anisotropy, optical properties, crystalline domains and thickness. The semiconducting thiophene-phenylene co-oligomer 1,4-bis(5'-hexyl-[2,2'-bithiophen]-5-yl)benzene (dHex-TTPTT) crystals were grown by solvent based self-assembly technique on silicon substrate with 300 nm thermally silicon dioxide. The ellipsometric measurements were performed with an Ep4-SE (Accurion). In an ellipsometric high-contrast image of the complete sample, we have localized high-quality single crystals. After demonstrating the uniaxial anisotropy of the crystal by using Müller-Matrix imaging ellipsometry, we determined the optical axes by rotating the sample and performed spectroscopic measurements (λ = 400-700 nm) in 5 nm intervals. The optical properties were described by using a Lorentz term in the Ep4-Model. After determining the dispersion of the crystals, we converted a recorded Delta and Psi-map into a 2D thickness image. Based on a quantitative analysis of the resulting thickness map, we have calculated the height of a molecular layer (3.49 nm).

Keywords: anisotropy, ellipsometry, SCFET, thin film

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Authors: Natnicha Hasoontree

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The purpose of this paper was to study the relationship between brand value and perceived brand quality of television viewers in Bangkok towards the television business in Thailand. The population included television viewers in Bangkok, Thailand. A probability sampling technique was performed to get a sample group that included 500 respondents. Taro Yamane technique was utilized to get a proper sample size. A five Likert scale questionnaire was designed specifically to investigate brand value and perceived brand quality from the perspectives of television viewers in Bangkok. The findings implied that consumers in Bangkok attached a high importance towards the brand equity of television companies that comprised brand ability, brand reputation, brand credibility, and business ethics. Perceived brand quality received high rank in all aspects.

Keywords: brand value, perceived brand quality, television business, television viewers

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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: Anthony D. Rhodes, Manan Goel

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We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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Authors: John Toussaint

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Objective: Our society is suffering from an epidemic of body image dissatisfaction, and related disorders appear to be increasing globally for children. There is much to indicate that children's body image and eating attitudes are being affected negatively by socio-cultural factors such as parents, peers and media. Most studies and theories, however, have focused extensively on the daughter-mother relationship. Very few studies have investigated the role of attachment to the father as an important factor in the development of girls’ and women’s attitudes towards themselves and their bodies. Recently, data have shown that the father’s parenting style, as well as the quality of the relationship with him is crucial for the understanding of the development and persistence of body image disorders. This presentation is based on samples of participants with self-defined body image dissatisfaction, and the self-reported measures of their fathers’ parental behaviours, emotional warmth, support, or protection. Attachment theory does offer support in exploring these relationships and it is used in this presentation to assist in understanding the relationship between the father and his daughter in relation to body image and mental health. Clinical implications are also offered in respect to work with body image, eating disorders and relational therapy. Methods: As awareness of the increasing frequency of body image concerns in children grows, so too does the need for a simple, valid and reliable measure of body image. The Children's Body Image Scale (CBIS) designed in Australia, depicts seven male and females figures from which children are to choose their perceived body type and ideal body type. This was compared with a range of international body mass index (BMI) reference standards. These measures together with individual one-on-one interviews were completed by 158 children aged 7-12 years. Results: A high frequency of body image dissatisfaction was indicated in the children's responses. 55% of girls and 41% of boys said they would like to be thinner, and wished for an ideal BMI figure below the 10th percentile. This is an unhealthy and unattainable level of body fatness for the majority of children when considered in relation to the reported secular trend of their increasing average body size. Thin children were generally ranked as best and perceived as kind, happy, academically skilled, and socially successful. Fat children were perceived as unintelligent, lazy, greedy, unpopular, and unable to play physical games. Conclusions: Body image ideals and fat stereotypes are well entrenched among children. There is much to indicate that children's body image and eating attitudes are being affected negatively by sociocultural factors such as parents, peers and media. Teachers and health professionals could promote intervention programs for children involving knowledge and acceptance of genetic influences on body type; the dangerous effects of weight loss dieting; the importance of physical activity and eating healthy; and scepticism and critical analysis of mass media messages.

Keywords: body image, father attachment, mental health, eating disorders

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Authors: Yuan-Hao Lee, Chia-Wei Lee, Ming-Fang Lin, Tzu-Huei Wu, Chih-Hsiang Ko, Wing P. Chan

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Computed tomography (CT) scan of the head is a good method for investigating cranial lesions. However, radiation-induced oxidative stress can be accumulated in the eyes and promote carcinogenesis and cataract. In this regard, we aimed to protect the eyes with barium sulfate shield(s) during CT scans and investigate the resultant image quality and radiation dose to the eye. Patients who underwent health examinations were selectively enrolled in this study in compliance with the protocol approved by the Ethics Committee of the Joint Institutional Review Board at Taipei Medical University. Participants’ brains were scanned with a water-based marker simultaneously by a multislice CT scanner (SOMATON Definition Flash) under a fixed tube current-time setting or automatic tube current modulation (TCM). The lens dose was measured by Gafchromic films, whose dose response curve was previously fitted using thermoluminescent dosimeters, with or without barium sulfate or bismuth-antimony shield laid above. For the assessment of image quality CT images at slice planes that exhibit the interested regions on the zygomatic, orbital and nasal bones of the head phantom as well as the water-based marker were used for calculating the signal-to-noise and contrast-to-noise ratios. The application of barium sulfate and bismuth-antimony shields decreased 24% and 47% of the lens dose on average, respectively. Under topogram-based TCM, the dose saving power of bismuth-antimony shield was mitigated whereas that of barium sulfate shield was enhanced. On the other hand, the signal-to-noise and contrast-to-noise ratios of DSCT images were decreased separately by barium sulfate and bismuth-antimony shield, resulting in an overall reduction of the CNR. In contrast, the integration of topogram-based TCM elevated signal difference between the ROIs on the zygomatic bones and eyeballs while preferentially decreasing the signal-to-noise ratios upon the use of barium sulfate shield. The results of this study indicate that the balance between eye exposure and image quality can be optimized by combining eye shields with topogram-based TCM on the multislice scanner. Eye shielding could change the photon attenuation characteristics of tissues that are close to the shield. The application of both shields on eye protection hence is not recommended for seeking intraorbital lesions.

Keywords: computed tomography, barium sulfate shield, dose saving, image quality

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Authors: Ado Ismail Sabo

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Statement of the Problem: The global trend in tertiary education institutions today is changing and moving towards engagement, promotion and marketing. The reason is to upscale reputation and impact positioning. More prominently, existing rivalry today seeks to draw-in the best and brightest students. A university or college is no longer just an institution of higher learning, but one adapting additional business nomenclature. Therefore, huge financial resources are invested by educational institutions to polish their image and improve their global and national ranking. In Nigeria, which boasts of a vast population of over 180 million people, some of whose patronage can bolster its education sector; standard of education continues to decline. Today, some Nigerian tertiary education institutions are shadows of their pasts, in terms of academic excellence. Quality has been relinquished because of the unquenchable quest by government officials, some civil servants, school heads and educators to amass wealth. It is very difficult to gain student satisfaction and their loyalty. Some of the student’s loyalties factor towards public higher educational institutions might be confusing. It is difficult to understand the extent to which students are satisfy on many needs. Some students might feel satisfy with the academic lecturers only, whereas others may want everything, and others will never satisfy. Due to these problems, this research aims to uncover the crucial factors influencing student loyalty and to examine if students’ satisfaction might impact mediate the relationship between service quality, organisational image and students’ loyalty towards public higher education institutions in Kano State, Nigeria. The significance of the current study is underscored by the paucity of similar research in the subject area and public tertiary education in a developing country like Nigeria as shown in existing literature. Methodology: The current study was undertaken by quantitative research methodology. Sample of 600 valid responses were obtained within the study population comprising six selected public higher education institutions in Kano State, Nigeria. These include: North West University Kano, Bayero University Kano, School of Management Studies Kano, School of Technology Kano, Sa’adatu Rimi College Kano and Federal College of Education (FCE) Kano. Four main hypotheses were formulated and tested using structural equation modeling techniques with Analysis of Moment Structure (AMOS Version 22.0). Results: Analysis of the data provided support for the main issue of this study, and the following findings are established: “Student Satisfaction mediates the relationship between Service Quality and Student Loyalty”, “Student Satisfaction mediates the relationship between Organizational Image and Student Loyalty” respectively. The findings of this study contributed to the theoretical implication which proposed a structural model that examined the relationships among overall Organizational image, service quality, student satisfaction and student loyalty. Conclusion: In addition, the findings offered a better insight to the managerial (higher institution of learning service providers) by focusing on portraying the image of service quality with student satisfaction in improving the quality of student loyalty.

Keywords: student loyalty, service quality, student satisfaction, organizational image

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Authors: Nartan Rajpriya

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City is a multiplex ecological system made up of social, economic and natural sub systems. Green space system is the foundation of the natural system. It is also suitable part of natural productivity in the urban structure. It is dispensable for constructing a high quality human settlements and a high standard ecocity. Ahmedabad is the fastest growing city of India. Today urban green space is under strong pressure in Ahmedabad city. Due to increasing urbanization, combined with a spatial planning policy of densification, more people face the prospect of living in less green residential environments. In this research analyzes the importance of available Green Space at Bodakdev Park, Ahmedabad, using remote sensing and GIS technologies. High resolution IKONOS image and LISS IV data has been used in this project. This research answers the questions like: • Temporal changes in urban green space area. • Proximity to heavy traffic or roads or any recreational facilities. • Importance in terms of health. • Availability of quality infrastructure. • Available green space per area, per sq. km and per total population. This projects incorporates softwares like ArcGIS, Ecognition and ERDAS Imagine, GPS technologies etc. Methodology includes the field work and collection of other relevant data while preparation of land use maps using the IKONOS imagery which is corrected using GPS.

Keywords: urban green space, ecocity, IKONOS, LISS IV

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Authors: Kyung-Hoon Jang, Jae-Hyo Park, Kwang-Yeop Jang, Dongjin Kim

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The Tesla coil is an electrical resonant transformer circuit designed by inventor Nikola Tesla in 1891. It is used to produce high voltage, low current and high frequency alternating current electricity. Tesla experimented with a number of different configurations consisting of two or sometimes three coupled resonant electric circuits. This paper focuses on development and high voltage education to apply a Tesla coil to cuisine for high quality flavor and taste conditioning as well as high voltage education under 50 kV corona discharge. The result revealed that the velocity of roasted black belly pork by Tesla coil is faster than that of conventional methods such as hot grill and steel plate etc. depending on applied voltage level and applied voltage time. Besides, carbohydrate and crude protein increased, whereas natrium and saccharides significantly decreased after lightning surge by Tesla coil. This idea will be useful in high voltage education and high voltage application.

Keywords: corona discharge, Tesla coil, high voltage application, high voltage education

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Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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Authors: Salim Çalışkan, Hakan Akyüz

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Digital image correlation has been accustomed as a versatile and efficient method for measuring displacements on the article surfaces by comparing reference subsets in undeformed images with the define target subset in the distorted image. The theoretical model points out that the accuracy of the digital image correlation displacement data can be exactly anticipated based on the divergence of the image noise and the sum of the squares of the subset intensity gradients. The digital image correlation procedure locates each subset of the original image in the distorted image. The software then determines the displacement values of the centers of the subassemblies, providing the complete displacement measures. In this paper, the effect of the speckle distribution and its effect on displacements measured out plane displacement data as a function of the size of the subset was investigated. Nine groups of speckle patterns were used in this study: samples are sprayed randomly by pre-manufactured patterns of three different hole diameters, each with three coverage ratios, on a computer numerical control punch press. The resulting displacement values, referenced at the center of the subset, are evaluated based on the average of the displacements of the pixel’s interior the subset.

Keywords: digital image correlation, speckle pattern, experimental mechanics, tensile test, aluminum alloy

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Mahsa Khani Oushani, Mohammad Kazem Hasanvand

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Text and image have always been two important components in Iranian layout. The interactive connection between text and image has shaped the art of book design with multiple patterns. In this research, first the structure and visual elements in the research data were analyzed and then the position of the text element and the image element in relation to each other based on Roland Barthes theory on the three theories of text and image, were studied and analyzed and the results were compared, and interpreted. The purpose of this study is to investigate the pattern of text and image in the works of Kamaluddin Behzad based on three Roland Barthes communication theories, 1. Descriptive communication, 2. Reference communication, 3. Matched communication. The questions of this research are what is the relationship between text and image in Behzad's works? And how is it defined according to Roland Barthes theory? The method of this research has been done with a structuralist approach with a descriptive-analytical method in a library collection method. The information has been collected in the form of documents (library) and is a tool for collecting online databases. Findings show that the dominant element in Behzad's drawings is with the image and has created a reference relationship in the layout of the drawings, but in some cases it achieves a different relationship that despite the preference of the image on the page, the text is dispersed proportionally on the page and plays a more active role, played within the image. The text and the image support each other equally on the page; Roland Barthes equates this connection.

Keywords: text, image, Kamaluddin Behzad, Roland Barthes, communication theory

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Authors: Maryam Azimi, Amin Banitalebi-Dehkordi, Yuanyuan Dong, Mahsa T. Pourazad, Panos Nasiopoulos

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While there exists a wide variety of Low Dynamic Range (LDR) quality metrics, only a limited number of metrics are designed specifically for the High Dynamic Range (HDR) content. With the introduction of HDR video compression standardization effort by international standardization bodies, the need for an efficient video quality metric for HDR applications has become more pronounced. The objective of this study is to compare the performance of the existing full-reference LDR and HDR video quality metrics on HDR content and identify the most effective one for HDR applications. To this end, a new HDR video data set is created, which consists of representative indoor and outdoor video sequences with different brightness, motion levels and different representing types of distortions. The quality of each distorted video in this data set is evaluated both subjectively and objectively. The correlation between the subjective and objective results confirm that VIF quality metric outperforms all to their tested metrics in the presence of the tested types of distortions.

Keywords: HDR, dynamic range, LDR, subjective evaluation, video compression, HEVC, video quality metrics

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Authors: Li Li, Ahmed A. Abd El-Latif, Aya El-Fatyany, Mohamed Amin

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This paper proposes a new secret image sharing method based on integer discrete cosine transform (IntDCT). It first transforms the original image into the frequency domain (DCT coefficients) using IntDCT, which are operated on each block with size 8*8. Then, it generates shares among each DCT coefficients in the same place of each block, that is, all the DC components are used to generate DC shares, the ith AC component in each block are utilized to generate ith AC shares, and so on. The DC and AC shares components with the same number are combined together to generate DCT shadows. Experimental results and analyses show that the proposed method can recover the original image lossless than those methods based on traditional DCT and is more sensitive to tiny change in both the coefficients and the content of the image.

Keywords: secret image sharing, integer DCT, lossless recovery, sensitivity

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: U. Ravi Babu, Mohd Mastan

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The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

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Authors: Kuo-Cheng Liu

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In the perceptual image coding, the objective is to shape the coding distortion such that the amplitude of distortion does not exceed the error visibility threshold, or to remove perceptually redundant signals from the image. While most researches focus on color image coding, the perceptual-based quantizer developed for luminance signals are always directly applied to chrominance signals such that the color image compression methods are inefficient. In this paper, the internal generative mechanism is integrated into the design of a color image compression method. The internal generative mechanism working model based on the structure-based spatial masking is used to assess the subjective distortion visibility thresholds that are visually consistent to human eyes better. The estimation method of structure-based distortion visibility thresholds for color components is further presented in a locally adaptive way to design quantization process in the wavelet color image compression scheme. Since the lowest subband coefficient matrix of images in the wavelet domain preserves the local property of images in the spatial domain, the error visibility threshold inherent in each coefficient of the lowest subband for each color component is estimated by using the proposed spatial error visibility threshold assessment. The threshold inherent in each coefficient of other subbands for each color component is then estimated in a local adaptive fashion based on the distortion energy allocation. By considering that the error visibility thresholds are estimated using predicting and reconstructed signals of the color image, the coding scheme incorporated with locally adaptive perceptual color quantizer does not require side information. Experimental results show that the entropies of three color components obtained by using proposed IGM-based color image compression scheme are lower than that obtained by using the existing color image compression method at perceptually lossless visual quality.

Keywords: internal generative mechanism, structure-based spatial masking, visibility threshold, wavelet domain

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Authors: Rachna Jain, Sushila Madan, Bindu Garg

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Cloud computing is the key powerhouse in numerous organizations due to shifting of their data to the cloud environment. In recent years it has been observed that cloud-based-services are being used on large scale for content storage, distribution and processing. Various issues have been observed in cloud computing environment that need to be addressed. Security and privacy are found topmost concern area. In this paper, a novel security model is proposed to secure data by utilizing CDN services like image to icon conversion. CDN Service is a content delivery service which converts an image to icon, word to pdf & Latex to pdf etc. Presented model is used to convert an image into icon by keeping image secret. Here security of image is imparted so that image should be encrypted and decrypted by data owners only. It is also discussed in the paper that how server performs multiplication and selection on encrypted data without decryption. The data can be image file, word file, audio or video file. Moreover, the proposed model is capable enough to multiply images, encrypt them and send to a server application for conversion. Eventually, the prime objective is to encrypt an image and convert the encrypted image to image Icon by utilizing homomorphic encryption.

Keywords: cloud computing, user data security, homomorphic encryption, image multiplication, CDN service

Procedia PDF Downloads 316

Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

Abstract:

In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

Procedia PDF Downloads 54

Authors: P. K. Telengech, K. Monjero, J. Maling’a, A. Nyende, S. Gichuki

Abstract:

There is need to identify an efficient protocol for use in extraction of high quality DNA for purposes of molecular work. Cassava roots are known for their high starch content, polyphenols and other secondary metabolites which interfere with the quality of the DNA. These factors have negative interference on the various methodologies for DNA extraction. There is need to develop a simple, fast and inexpensive protocol that yields high quality DNA. In this improved Dellaporta method, the storage roots are lyophilized to reduce the water content; the extraction buffer is modified to eliminate the high polyphenols, starch and wax. This simple protocol was compared to other protocols intended for plants with similar secondary metabolites. The method gave high yield (300-950ng) and pure DNA for use in PCR analysis. This improved Dellaporta protocol allows isolation of pure DNA from starchy cassava storage roots.

Keywords: cassava storage roots, dellaporta, DNA extraction, lyophilisation, polyphenols secondary metabolites

Procedia PDF Downloads 319

Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

Abstract:

The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

Procedia PDF Downloads 127

Authors: P. Karthick, K. Mahesh

Abstract:

Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 163

Authors: Ketwadee Madden

Abstract:

Product or service image is among the vital factors that predict individuals’ choice of buying a product or services, goes to a place or attached to a person. Similarly, in the context of tourism, the destination image is a very important factor to which tourist considers before making their tour destination decisions. In light of this, the objective of this study is to conceptually investigate among French tourists, the determinants of Thailand’s tourism destination image. For this objective to be achieved, prior studies were reviewed, leading to the development of conceptual framework highlighting the determinants of destination image. In addition, this study develops some hypotheses that are to be empirically investigated. Aside these, based on the conceptual findings, suggestions on how to motivate European tourists to chose Thailand as their preferred tourism destination were made.

Keywords: cognitive destination image, affective destination image, motivations, risk perception, word of mouth

Procedia PDF Downloads 110