Search results for: image entropy

Authors: Biji Jacob

Abstract:

Vector quantization algorithm which uses minimum distance calculation for codebook generation, a time consuming calculation performed on each pixel values leads to computation complexity. The codebook is updated by comparing the distance of each vector to their centroid vector and measure for their closeness. In this paper vector quantization is modified based on vector difference algorithm for image enhancement purpose. In the proposed scheme, vector differences between the vectors are considered as the new generation vectors or new codebook vectors. The codebook is updated by comparing the new generation vector with a threshold value having minimum error with the parent vector. The minimum error decides the fitness of each newly generated vector. Thus the codebook is generated in an adaptive manner and the fitness value is determined for the suppression of the degraded portion of the image and thereby leads to the enhancement of the image through the adaptive searching capability of the vector quantization through vector difference algorithm. Experimental results shows that the vector difference scheme efficiently modifies the vector quantization algorithm for enhancing the image with peak signal to noise ratio (PSNR), mean square error (MSE), Euclidean distance (E_dist) as the performance parameters.

Keywords: codebook, image enhancement, vector difference, vector quantization

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Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

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Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector

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Authors: Yu Zhang, Kohei Inoue, Kiichi Urahama

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We propose a simplified bilateral filter with binarized coefficients for accelerating it. Its computational cost is further decreased by sampling pixels. This computationally low cost filter is useful for smoothing or denoising images by using mobile devices with limited computational power.

Keywords: bilateral filter, binarized-weight bilateral filter, image smoothing, image denoising, pixel sampling

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Authors: P. Strakos, M. Jaros, T. Karasek, T. Kozubek, P. Vavra, T. Jonszta

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In medical imaging, segmentation of different areas of human body like bones, organs, tissues, etc. is an important issue. Image segmentation allows isolating the object of interest for further processing that can lead for example to 3D model reconstruction of whole organs. Difficulty of this procedure varies from trivial for bones to quite difficult for organs like liver. The liver is being considered as one of the most difficult human body organ to segment. It is mainly for its complexity, shape versatility and proximity of other organs and tissues. Due to this facts usually substantial user effort has to be applied to obtain satisfactory results of the image segmentation. Process of image segmentation then deteriorates from automatic or semi-automatic to fairly manual one. In this paper, overview of selected available software applications that can handle semi-automatic image segmentation with further 3D volume reconstruction of human liver is presented. The applications are being evaluated based on the segmentation results of several consecutive DICOM images covering the abdominal area of the human body.

Keywords: image segmentation, semi-automatic, software, 3D volumetric reconstruction

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Authors: Mohsen Masoomi, Fazel Asadi Amjad, Monireh Arvin

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According to Naturalistic principles, human destiny in the form of blind chance and determinism, entraps the individual, so man is a defenceless creature unable to escape from the ruthless paws of a stoical universe. In Naturalism; nonetheless, melodrama mirrors a conscious alternative with a peculiar function. A typical American Naturalistic character thus cannot be a subject for social criticism of American society since they are not victims of the ongoing virtual slavery, capitalist system, nor of a ruined milieu, but of their own volition, and more importantly, their character frailty. Through a Postmodern viewpoint, each Naturalistic work can encompass some entropic trends and changes culminating in an entire failure and devastation. Frank Norris in McTeague displays the futile struggles of ordinary men and how they end up brutes. McTeague encompasses intoxication, abuse, violation, and ruthless homicides. Norris’ depictions of the falling individual as a demon represent the entropic dimension of Naturalistic novels. McTeague’s defeat is somewhat his own fault, the result of his own blunders and resolution, not the result of sheer accident. Throughout the novel, each character is a kind of insane quester indicating McTeague’s decadence and, by inference, the decadence of Western civilisation. McTeague seems to designate Norris’ solicitude for a community fabricated by the elements of human negative demeanours and conducts hauling acute symptoms of infectious dehumanisation. The aim of this article is to illustrate how one specific negative human disposition gradually, like a running fire, can spread everywhere and burn everything in itself. The author applies the concept of entropy metaphorically to describe the individual devolutions that necessarily comprise community entropy in McTeague, a dying universe.

Keywords: animal imagery, entropy, Gypsy, melodrama

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Authors: Noah R. Fram

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Although it has been confirmed by multiple studies, the inverted-U relationship between stimulus complexity and preference (liking) remains contentious. Research aimed at substantiating the model are largely reliant upon anecdotal self-assessments of subjects and basic measures of complexity, leaving potential confounds unresolved. This study attempts to address the topic by assessing listening time as a behavioral correlate of liking (with the assumption that engagement prolongs listening time) and by looking for latent factors underlying several measures of rhythmic complexity. Participants listened to groups of rhythms, stopping each one when they started to lose interest and were asked to rate each rhythm in each group in terms of interest, complexity, and preference. Subjects were not informed that the time spent listening to each rhythm was the primary measure of interest. The hypothesis that listening time does demonstrate the same inverted-U relationship with complexity as verbal reports of liking was confirmed using a variety of metrics for rhythmic complexity, including meter-dependent measures of syncopation and meter-independent measures of entropy.

Keywords: complexity, entropy, rhythm, syncopation

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Chih-Wen Wu

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This study examines the antecedents of heritage tourism loyalty and its relation to destination image, consumer travel experience, and destination satisfaction in the tourism context. In this respect, a number of important questions concerning how destination image, consumer travel experience, and destination satisfaction impact destination loyalty are raised. This study attempts to identify three key antecedents of loyalty in the heritage context. The author empirically tests predicted relationships by using personal interview data from 475 foreign tourists. The conceptual model investigated the relevant relationships among the constructs by using confirmatory factor analysis(CFA) and structural equation modeling (SEM) approach. Findings from the research sample support the argument that destination image, consumer travel experience, destination satisfaction are the key determinants of destination loyalty. Destination image and consumer travel experience influence destination satisfaction. The author also discusses theoretical and managerial implications of research findings for marketing the heritage globally.

Keywords: heritage, destination loyalty, destination image, consumer travel experience, destination satisfaction, tourism

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Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Hyeon-Seung Kim, Bit-Na Cho, Tae-Woon Jeong, Soo-Young Yoon, Leen-Seok Kang

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Recently, a construction project has been large in the size and complicated in the site work. The web-cameras are used to manage the construction site of such a large construction project. They can be used for monitoring the construction schedule as compared to the actual work image of the planned work schedule. Specially, because the 4D CAD system that the construction appearance is continually simulated in a 3D CAD object by work schedule is widely applied to the construction project, the comparison system between the real image of actual work appearance by web-camera and the simulated image of planned work appearance by 3D CAD object can be an intelligent construction schedule management system (ICON). The delayed activities comparing with the planned schedule can be simulated by red color in the ICON as a virtual reality object. This study developed the ICON and it was verified in a real bridge construction project in Korea. To verify the developed system, a web-camera was installed and operated in a case project for a month. Because the angle and zooming of the web-camera can be operated by Internet, a project manager can easily monitor and assume the corrective action.

Keywords: 4D CAD, web-camera, ICON (intelligent construction schedule management system), 3D object image

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

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Authors: Agastya Pratap Singh

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Generative Adversarial Networks (GANs) have emerged as powerful tools in the fields of image recognition and anomaly detection due to their ability to model complex data distributions and generate realistic images. This systematic review explores recent advancements and applications of GANs in both image recognition and anomaly detection tasks. We discuss various GAN architectures, such as DCGAN, CycleGAN, and StyleGAN, which have been tailored to improve accuracy, robustness, and efficiency in visual data analysis. In image recognition, GANs have been used to enhance data augmentation, improve classification models, and generate high-quality synthetic images. In anomaly detection, GANs have proven effective in identifying rare and subtle abnormalities across various domains, including medical imaging, cybersecurity, and industrial inspection. The review also highlights the challenges and limitations associated with GAN-based methods, such as instability during training and mode collapse, and suggests future research directions to overcome these issues. Through this review, we aim to provide researchers with a comprehensive understanding of the capabilities and potential of GANs in transforming image recognition and anomaly detection practices.

Keywords: generative adversarial networks, image recognition, anomaly detection, DCGAN, CycleGAN, StyleGAN, data augmentation

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Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

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Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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Authors: Hamidreza Joudaki, Yousefali Ziari

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The appearance of city and urbanism is one of the important processes which have affected social communities. Being industrialized urbanism developed along with each other in the history. In addition, they have had simple relationship for more than six thousand years, that is, from the appearance of the first cities. In 18th century by coming out of industrial capitalism, progressive development took place in urbanism in the world. In Iran, the city of each region made its decision by itself and the capital of region (downtown) was the only central part and also the regional city without any hierarchy, controlled its realm. However, this method of ruling during these three decays, because of changing in political, social and economic issues that have caused changes in rural and urban relationship. Moreover, it has changed the variety of performance of cities and systematic urban network in Iran. Today, urban system has very vast imbalanced apace and performance. In Isfahan, the trend of urbanism is like the other part of Iran and systematic urban hierarchy is not suitable and normal. This article is a quantitative and analytical. The statistical communities are Isfahan Province cities and the changes in urban network and its hierarchy during the period of fifty years (1956 -2006) has been surveyed. In addition, those data have been analyzed by model of Rank and size and Entropy index. In this article Iran cities and also the factor of entropy of primate city and urban hierarchy of Isfahan Province have been introduced. Urban residents of this Province have been reached from 55 percent to 83% (2006). As we see the analytical data reflects that there is mismatching and imbalance between cities. Because the entropy index was.91 in 1956.And it decreased to.63 in 2006. Isfahan city is the primate city in the whole of these periods. Moreover, the second and the third cities have population gap with regard to the other cities and finally, they do not follow the system of rank-size.

Keywords: urban network, urban hierarchy, primate city, Isfahan province, urbanism, first cities

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Authors: Yili Chen, Xiaokun Liang, Zhicheng Zhang, Yaoqin Xie

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In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern.

Keywords: retinal prosthesis, image processing, region of interest, saliency map, trimming threshold selection

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Authors: Lauren Currell, Gemma Hurst

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Introduction: The present study experimentally investigated the impact of attractive Instagram images on female’s body image. It also examined whether physical appearance perfectionism and cognitive coping predicted body image following upward comparisons to idealised bodies on Instagram. Methods: One-hundred and fifty-eight females (mean age 24.35 years) were randomly assigned to an experimental (where they compared their bodies to those of Instagram models) or control condition (where they critiqued landscape painting). All participants completed measures on physical appearance perfectionism, cognitive coping, and pre- and post-measures of body image. Results: Comparing one’s body to idealised bodies on Instagram resulted in increased appearance and weight dissatisfaction and decreased confidence, compared to the control condition. Physical appearance perfectionism and cognitive coping both predicted body image outcomes for the experimental condition. Discussion: Clinical implications, such as the prevention and treatment of body dissatisfaction, are discussed. Strengths and limitations of the current study are also noted, and suggestions for future research are provided.

Keywords: perfectionism, cognitive coping, body image, social media

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Risti Suryantari, Flaviana

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The aim of this research is to design calibration method of Thermochromic Liquid Crystal for temperature distribution measurement based on mathematical morphology of hue image A glass of water is placed on the surface of sample TLC R25C5W at certain temperature. We use scanner for image acquisition. The true images in RGB format is converted to HSV (hue, saturation, value) by taking of hue without saturation and value. Then the hue images is processed based on mathematical morphology using Matlab2013a software to get better images. There are differences on the final images after processing at each temperature variation based on visualization observation and the statistic value. The value of maximum and mean increase with rising temperature. It could be parameter to identify the temperature of the human body surface like hand or foot surface.

Keywords: thermochromic liquid crystal, TLC, mathematical morphology, hue image

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Authors: Livia Eisler, Cristiane C. B. Alves, Cristina L. F. Ortolani, Kurt Faltin Jr.

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Purpose: This paper proposes a technically simple diagnosis method among orthodontists and maxillofacial surgeons in order to evaluate discrete bone alterations. The methodology consists of a protocol to optimize the diagnosis and minimize the possibility for orthodontic and ortho-surgical retreatment. Materials and Methods: A protocol of image processing and analysis, through ImageJ software and its plugins, was applied to 20 pairs of lateral cephalometric images obtained from cone beam computerized tomographies, before and 1 year after undergoing orthognathic surgery. The optical density of the images was analyzed in the condylar region to determine possible bone alteration after surgical correction. Results: Image density was shown to be altered in all image pairs, especially regarding the condyle contours. According to measures, condyle had a gender-related density reduction for p=0.05 and condylar contours had their alterations registered in mm. Conclusion: A simple, viable and cost-effective technique can be applied to achieve the more detailed image-based diagnosis, not depending on the human eye and therefore, offering more reliable, quantitative results.

Keywords: bone resorption, computer-assisted image processing, orthodontics, orthognathic surgery

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Mahadzirah Mohamad, Nur Izzati Ab Ghani

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Worldwide, tourism sustained growth and remained to be one of the fast-growing sectors. Malaysia tourism industry experienced an unstable and declining pattern of international tourist arrival’s growth rate. The situation suggested that the industry was competitive and denoted the need to study factors that influence tourist loyalty. The primary purpose of this study was to develop a model that examined how destination image, perceived value, service quality and tourist satisfaction affect destination loyalty. The study was conducted at the Kuala Lumpur International Airport and Kota Kinabalu International Airport. The respondents were international tourists from United Kingdom and Australia and they were selected using simple random sampling method. A total of 337 respondents were subjected to data analysis using structural equation modelling. The study uncovered that perceived value and destination image was highly correlated and the model suggested that these constructs should be treated as one construct. The construct was labelled as overall destination image. Overall image had significant direct effect on service quality, satisfaction and loyalty. Service quality had a significant indirect effect on loyalty through satisfaction as a moderating variable. However, satisfaction had no mediating effect on the relationship between overall destination image and loyalty. The study suggested that more efforts should be focused on portraying the image of experiencing joy with many interesting natural scenic places to see whilst on a holiday to Malaysia. In addition, the destination management office should promote tourist visiting to Malaysia would enjoy quality service related to accommodation, information facilities, health, and shopping. Tourist satisfaction empirically proved to be an important construct that influenced destination loyalty. This study contributed to the extended knowledge that postulated overall image of a destination was measured by perceived value and destination image.

Keywords: destination image, destination loyalty, structural equation modelling, tourist satisfaction

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Authors: Samira Eskandari

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The image of Tehran has been impacted in recent years due to poor urban management and fragmented governance. There is no cohesive urban beautification framework in Tehran to enforce builders take aesthetic factors seriously when design and construct new buildings. The existing guidelines merely provide people with recommendations, not regulations. Obviously, Tehran needs a more comprehensive and strict urban beautification framework to restore its image. The damaged image has impacted the city’s social, economic and environmental growth. This research aims to find and examine a solution by which the employment of urban beautification regulation would be guaranteed, and city image would be organized. The methodology is based on a qualitative approach associated with analytical methods, in-depth surveys and interviews with Tehran citizens, authorities and experts, and use of academic resources as well as simulation. As a result, one practical solution is to incorporate aesthetic guidelines into a survival-related framework like a seismic guideline. Tehran is a seismic site, and all the buildings in Tehran have to be retrofitted against earthquake during construction. Hence, by integrating seismic regulations and aesthetic disciplines, urban beautification will be somehow guaranteed. Besides, the seismic image can turn into Tehran’s brand and enhances city identity. This research is trying to increase the social, environmental, and economic interconnectedness between urban planning and seismic planning by the usage of landscape architecture methods. As a case study, the potential outcomes are simulated in Tajrish, a suburb located in the north of Tehran. The result is that, by the redefinition of the morphology of seismic retrofitting systems, used in the significant city image elements, and re-function them in accordance with the Iranian culture and traditions, the city image would become more harmonized and legible.

Keywords: earthquake, retrofitting systems, Tehran image, urban beautification

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Authors: Neetu Manocha

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Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

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Authors: Wanida Suwunniponth

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The purposes of this research were to investigate the perceived of a cultural image and loyalty of tourists toward the attraction at Banglumphu neighborhood in Bangkok and to study the relationship of the cultural image of Banglumphu community and loyalty to visit this area of the tourists. This study employed both quantitative approach and qualitative approach. In a quantitative research, a questionnaire was used to collect data from 300 systematic sampled tourists who visited Banglumphu area and the correlation analysis were used to analyze data. The results revealed that the overall tourists’ point of view toward Banglumphu cultural image was at a good level which lifestyle had the best image, followed by value and belief, physical dimension, community identity, tradition, and local wisdom. In addition, the overall aspect of tourists’ loyalty including satisfaction, word of mouths, and revisiting were at good levels which word of mouths received the highest value, followed by revisiting, and satisfaction, respectively. In addition, the relationship between cultural image in aspect on lifestyle, tradition, local wisdom, belief, community identity and loyalty to visit Banglumphu in each aspect on satisfaction, word of mouths, and revisiting were moderately correlated at the significant level of 0.05, except physical dimension was not correlated with each aspect of tourists’ loyalty.

Keywords: cultural tourism, image, loyalty, revisit

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Authors: Mohamed Salah Azzaz, Camel Tanougast, Tarek Hadjem

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In this paper, a new low-cost image encryption technique is proposed and analyzed. The developed chaos-based key generator provides complex behavior and can change it automatically via a random-like switching rule. The designed encryption scheme is called PCSS (Parametric Chaos-based Switching System). The performances of this technique were evaluated in terms of data security and privacy. Simulation results have shown the effectiveness of this technique, and it can thereafter, ready for a hardware implementation.

Keywords: chaos, encryption, security, image

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Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

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Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure mapping systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of flexible sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the users' needs.

Keywords: dynamic cushion, image processing, pressure mapping system, wheelchair

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Authors: W. S. Besbas, M. A. Artemi, R. M. Salman

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Content based face sketch retrieval can be used to find images of criminals from their sketches for 'Crime Prevention'. This paper investigates the problem of CBIR of face sketch images in transform domain. Face sketch images that are similar to the query image are retrieved from the face sketch database. Features of the face sketch image are extracted in the spectrum domain of a selected transforms. These transforms are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Walsh Hadamard Transform (WHT). For the performance analyses of features selection methods three face images databases are used. These are 'Sheffield face database', 'Olivetti Research Laboratory (ORL) face database', and 'Indian face database'. The City block distance measure is used to evaluate the performance of the retrieval process. The investigation concludes that, the retrieval rate is database dependent. But in general, the DCT is the best. On the other hand, the WHT is the best with respect to the speed of retrieving images.

Keywords: Content Based Image Retrieval (CBIR), face sketch image retrieval, features selection for CBIR, image retrieval in transform domain

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Authors: T. R. Sharika, Ashwini Kumar, Kamal Bijlani

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Encryption is the process of converting crucial information’s unreadable to unauthorized persons. Image security is an important type of encryption that secures all type of images from cryptanalysis. A stream cipher is a fast symmetric key algorithm which is used to convert plaintext to cipher text. In this paper we are proposing an image encryption algorithm with Discrete Cosine Transform and Stream Ciphers that can improve compression of images and enhanced security. The paper also explains the use of a shuffling algorithm for enhancing securing.

Keywords: decryption, DCT, encryption, RC4 cipher, stream cipher

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Authors: Toktam Khatibi

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Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.

Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers

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Authors: Marilyn U. Balagtas, Maria Ruth M. Regalado, Carmelina E. Barrera, Ramer V. Oxiño, Rosarito T. Suatengco, Josephine E. Tondo

Abstract:

This study presents the perceptions of the students and teachers from kindergarten to tertiary level of the image of the 21st century teacher to provide basis in designing teacher development programs in Teacher Education Institutions (TEIs) in the Philippines. The highlights of the report are the personal, psychosocial, and professional images of the 21st century teacher in basic education and the teacher educators based on a survey done to 612 internal stakeholders of nine member institutions of the National Network of Normal Schools (3NS). Data were obtained through the use of a validated researcher-made instrument which allowed generation of both quantitative and qualitative descriptions of the teacher image. Through the use of descriptive statistics, the common images of the teacher were drawn, which were validated and enriched by the information drawn from the qualitative data. The study recommends a repertoire of teacher development programs to create the good image of the 21st century teachers for a better Philippines.

Keywords: teacher image, 21st century teacher, teacher education, development program

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