Search results for: image processing

Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: T. G. Asmitha Chandini

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Web-based image search re-ranking, as an successful method to get better the results. In a query keyword, the first stair is store the images is first retrieve based on the text-based information. The user to select a query keywordimage, by using this query keyword other images are re-ranked based on their visual properties with images.Now a day to day, people projected to match images in a semantic space which is used attributes or reference classes closely related to the basis of semantic image. though, understanding a worldwide visual semantic space to demonstrate highly different images from the web is difficult and inefficient. The re-ranking images, which automatically offline part learns dissimilar semantic spaces for different query keywords. The features of images are projected into their related semantic spaces to get particular images. At the online stage, images are re-ranked by compare their semantic signatures obtained the semantic précised by the query keyword image. The query-specific semantic signatures extensively improve both the proper and efficiency of image re-ranking.

Keywords: Query, keyword, image, re-ranking, semantic, signature

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Authors: Shih-Heng Tung, Ming-Hsiang Shih, Wen-Pei Sung

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Because of the rapid development of digital camera and computer, digital image correlation method has drawn lots of attention recently and has been applied to a variety of fields. However, the image distortion is inevitable when the image is captured through a lens. This image distortion problem can result in an innegligible error while using digital image correlation method. There are already many different ways to correct the image distortion, and most of them require specific image patterns or precise control points. A new distortion correction method is proposed in this study. The proposed method is based on the fact that a flat surface should keep flat when it is measured using three-dimensional (3D) digital image measurement technique. Lens distortion can be divided into radial distortion, decentering distortion and thin prism distortion. Because radial distortion has a more noticeable influence than the other types of distortions, this method deals only with radial distortion. The simplified 3D digital image measurement technique is adopted to measure the surface coordinates of a flat specimen. Then the gradient method is applied to find the best correction parameters. A few experiments are carried out in this study to verify the correctness of this method. The results show that this method can achieve a good accuracy and it is suitable for both large and small distortion conditions. The most important advantage is that it requires neither mark with specific pattern nor precise control points.

Keywords: 3D DIC, radial distortion, distortion correction, planarity

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Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

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Authors: Dora Bianchi, Anthony Schinelli, Laura Maria Fatta, Antonia Lonigro, Fabio Lucidi, Fiorenzo Laghi

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Purpose: The role of body image in adolescent binge eating is widely confirmed, albeit the various facets of this relationship are still mostly unexplored. Within the multidimensional body image framework, this study hypothesized the indirect effects of three body image coping strategies (positive rational acceptance, appearance fixing, avoidance) in the expected relationship between the perceived impact of body image on individuals’ quality of life and binge eating symptoms. Methods: Participants were 715 adolescents aged 15-21 years (49.1% girls) recruited in Italian schools. An anonymous self-report online survey was administered. A multiple mediation model was tested. Results: A more positive perceived impact of body image on quality of life was a negative predictor of adolescents’ binge eating, controlling for individual levels of body satisfaction. Three indirect effects were found in this relationship: on one hand, the positive body image impact reduced binge eating via increasing positive rational acceptance (M1), and via reducing avoidance (M2); on the contrary, the positive body image impact also enhanced binge eating via increasing appearance fixing (M3). Conclusions: The body image impact on quality of life can be alternatively protective—when adaptive coping is solicited, and maladaptive strategies are reduced—or a risk factor, which may increase binge eating by soliciting appearance fixing.

Keywords: binge eating, body image satisfaction, quality of life, coping strategies, adolescents

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Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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Authors: P. Gil, F. Charrua-Santos, A. A. Baptista, S. Azevedo, A. Espirito-Santo, J. Páscoa

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Lean manufacturing is a philosophy of industrial management that aims to identify and eliminate any waste that exists in the companies. The augmented reality is a new technology that stills being developed in terms of software and hardware. This technology consists of an image capture device, a device for data processing and an image visualization equipment to visualize collected and processed images. It is characterized by being a technology that merges the reality with the virtual environment, so there is an instantaneous interaction between the two environments. The present work intends to demonstrate that the use of the augmented reality will contribute to improve some tools and methods used in Lean manufacturing philosophy. Through several examples of application in industry it will be demonstrated that the technological impact of the augmented reality on the Lean Manufacturing philosophy contribute to added value improvements.

Keywords: lean manufacturing, augmented reality, case studies, value

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Authors: Maria Grazia Albanesi, Riccardo Amadeo

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This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue.

Keywords: eye-tracking, image quality assessment metric, MOS, quality of user experience, visual perception

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Geeta Kasana, Kulbir Singh, Satvinder Singh

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In this paper, a steganographic scheme for digital images using Integer Wavelet Transform (IWT) is proposed. The cover image is decomposed into wavelet sub bands using IWT. Each of the subband is divided into blocks of equal size and secret data is embedded into the largest and smallest pixel values of each block of the subband. Visual quality of stego images is acceptable as PSNR between cover image and stego is above 40 dB, imperceptibility is maintained. Experimental results show better tradeoff between capacity and visual perceptivity compared to the existing algorithms. Maximum possible error analysis is evaluated for each of the wavelet subbands of an image.

Keywords: DWT, IWT, MSE, PSNR

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Authors: Vajiheh Javani

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The study aims to examine brand image in Iran's professional Football League (2014-2015). The study was descriptive survey one. A sample of Iranian professional football league fans (N=911) responded four items questionnaire. A structural equation model (SEM) test with maximum likelihood estimation was performed to test the relationships among the research variables. The analyses of data showed three dimensions of brand image influenced on fan’s brand loyalty of which the attitude was the most important. Benefits and attributes were placed in the second and third rank respectively. According to results, brand image plays a pivotal role between Iranian fans brand loyalty. Create an attractive and desirable brand image in the fans mind increases brand loyalty. Moreover due to, revenue and profits increase through ticket sales and products of club and also attract more sponsors.

Keywords: brand management, sport industry, brand image, fans

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Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma

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Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.

Keywords: image fusion, pyramid, wavelets, principal component analysis

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Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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Authors: Nimit Soonsan

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Hotel image is a key business issue in today’s hotel market and has been increasingly been recognized as a valuable and inimitable source of competitive advantage by many hotel. The current study attempted to develop and test a relationship of hotel image, overall satisfaction, and future behavior. Based on the above concepts, this paper hypothesizes the correlations among four constructs, namely, hotel image and overall satisfaction as antecedents of future behavior that positive word-of-mouth and intention to revisit. This study surveyed for a sample of 244 international customers staying budget hotel in Phuket, Thailand and using a structural equation modeling identified relationship between hotel image, overall satisfaction and future behavior. The major finding of structural equation modeling indicates that hotel image directly affects overall satisfaction and indirectly affects future behavior that positive word-of-mouth and intention to revisit. In addition, overall satisfaction had significant influence on future behavior that positive word-of-mouth and intention to revisit, and the mediating role of overall satisfaction is also confirmed in this study. Managerial implications are provided, limitations noted, and future research directions suggested.

Keywords: hotel image, satisfaction, word-of-mouth, revisit

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Authors: Joshua Buli, David Pietrowski, Samuel Britton

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Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.

Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Luciana Brandao Ferreira, Janaina de Moura Engracia Giraldi, Fabiana Gondim Mariutti, Marina Toledo de Arruda Lourencao

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Developing countries, such as BRICS (Brazil, Russia, India, China and South Africa) are hosting sports mega-events to promote socio-economic development and image enhancement. Thus, this paper aims to verify the image of Rio de Janeiro, in Brazil, as the host city of 2016 Olympic Games, considering the main cognitive and affective image dimensions. The research design uses exploratory factorial analysis to find the most important factors highlighted in the city image dimensions. The data were collected by structured questionnaires with an international respondents sample (n=274) with high international travel experience. The results show that Rio’s image as a sport mega-event host city has two main factors in each dimension: Cognitive ('General Infrastructure'; 'Services and Attractions') and Affective ('Positive Feelings'; 'Negative Feelings'). The most important factor related to cognitive dimension was 'Services and Attractions' which is more related to tourism activities. In the affective dimension 'Positive Feelings' was the most important factor, which means a good result considering that is a city in an emerging country with many unmet social demands.

Keywords: Rio de Janeiro, 2016 olympic games, host city image, cognitive image dimension, affective image dimension

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Authors: Danuta Szwajca

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Image is a very important intangible asset of a contemporary enterprise, especially, in case of a bank as a public trust institution. A positive, demanded image may effectively distinguish the bank among the competition and build the customer confidence and loyalty. PKO BP is the biggest and largest bank functioning on the Polish financial market. Within the years not a very nice image of the bank has been embedded in the customers’ minds as an old-fashioned, stagnant, resistant to changes institution, what result in the customer loss, and ageing. For this reason, in 2010, the bank launched a campaign of radical image change along with a strategy of branches modernization and improvement of the product offer. The objective of the article is to make an attempt of effectiveness assessment of the brand repositioning campaign that lasted three years. The foundations of the assessment are the results of the questionnaire research concerning the way of bank’s perception before and after the campaign.

Keywords: advertising campaign, brand repositioning, image of the bank, repositioning

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Authors: Olaiya Folorunsho, Comfort Y. Daramola, Joel N. Ugwu, Lawrence B. Adewole, Olufisayo S. Ekundayo

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In today world, there is a tremendous rise in the usage of internet due to the fact that almost all the communication and information sharing is done over the web. Conversely, there is a continuous growth of unauthorized access to confidential data. This has posed a challenge to information security expertise whose major goal is to curtail the menace. One of the approaches to secure the safety delivery of data/information to the rightful destination without any modification is steganography. Steganography is the art of hiding information inside an embedded information. This research paper aimed at designing a secured algorithm with the use of image steganographic technique that makes use of Least Significant Bit (LSB) algorithm for embedding the data into the bit map image (bmp) in order to enhance security and reliability. In the LSB approach, the basic idea is to replace the LSB of the pixels of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The system was implemented using C# programming language of Microsoft.NET framework. The performance evaluation of the proposed system was experimented by conducting a benchmarking test for analyzing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result showed that image steganography performed considerably in securing data hiding and information transmission over the networks.

Keywords: steganography, image steganography, least significant bits, bit map image

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Authors: Koushlendra Kumar Singh, Manish Kumar Bajpai, Rajesh K. Pandey

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The edges of low contrast images are not clearly distinguishable to the human eye. It is difficult to find the edges and boundaries in it. The present work encompasses a new approach for low contrast images. The Chebyshev polynomial based fractional order filter has been used for filtering operation on an image. The preprocessing has been performed by this filter on the input image. Laplacian of Gaussian method has been applied on preprocessed image for edge detection. The algorithm has been tested on two test images.

Keywords: low contrast image, fractional order differentiator, Laplacian of Gaussian (LoG) method, chebyshev polynomial

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Authors: Sawitree Suvanno

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The objective of this study is to investigate the Suan Sunandha Rajabhat University (SSRU) image among people in Bangkok. This study was conducted in the quantitative research and the questionnaires were used to collect data from 360 people of a sample group. Descriptive and inferential statistics were used in data analysis. The result showed that the SSRU’s image among people in Bangkok is in the “rather true” level of questionnaire scale in all aspects measured. The aspect that gains the utmost average is that the university is considered as royal-oriented and conservative; 2) the instructional supplies, buildings and venue promoting Thai art and tradition; 3) the moral and honest university administration; 4) the curriculum and the skillful students as well as graduates. Additional, people in Bangkok with different profession have the different view to the SSRU’s image at the significant level 0.05; there is no significant difference in gender, age and income.

Keywords: Bangkok, demographics, image, Suan Sunandha Rajabhpat University

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Authors: Daira Radouane, Naim Boudmagh, Hamada Adel

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The but of this handling is to use the technique of the shearing with a mechanism lapping machine of image: a prism of Wollaston. We want to characterize this prism in order to be able to employ it later on in an analysis by shearing. A prism of Wollaston is a prism produced in a birefringent material i.e. having two indexes of refraction. This prism is cleaved so as to present the directions associated with these indices in its face with entry. It should be noted that these directions are perpendicular between them.

Keywords: non destructive control, aluminium, interferometry, treatment of image

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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The mobile phone has no longer confined to communication, from the aspect of smartphones, consumers are only willing to pay for the product which the added value has corresponded with their appetites, such as multiple application, upgrade of the camera, and the appearance of the phone and so on. Moreover, as the maturity stage of smartphone industry today, the strategy which manufactures used to gain competitive advantages through hardware as well as software differentiation, is no longer valid. Thus, this research aims to initiate from brand image, to examine exactly whether consumers’ buying intention focus on smartphone brand or operating system, at the same time, perceived value and customer satisfaction will be added between brand image and continuous usage intention to investigate the impact of these two facets toward continuous usage intention. This study verifies the correlation, fitness, and relationship between the variables that lies within the conceptual framework. The result of using structural equation modeling shows that brand image has a positive impact on continuous usage intention. Firms can affect consumer perceived value and customer satisfaction through the creation of the brand image. It also shows that the brand image of smartphone and brand image of the operating system have a positive impact on customer perceived value and customer satisfaction. Furthermore, perceived value also has a positive impact on satisfaction, and so is the relation within satisfaction and perceived value to the continuous usage intention. Last but not least, the brand image of the smartphone has a more remarkable impact on customers than the brand image of the operating system. In addition, this study extends the results to management practice and suggests manufactures to provide fine product design and hardware.

Keywords: smartphone, brand image, perceived value, continuous usage intention

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Justie Su-Tzu Juan, Ming-Jheng Li, Ching-Fen Lee, Ruei-Yu Wu

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A secret image sharing scheme is a way to protect images. The main idea is dispersing the secret image into numerous shadow images. A secret image sharing scheme can withstand the impersonal attack and achieve the highly practical property of multiuse  is more practical. Therefore, this paper proposes a verifiable and detectable secret image-sharing scheme called VDGMSISS to solve the impersonal attack and to achieve some properties such as encrypting multi-secret images at one time and multi-use. Moreover, our scheme can also be used for any genera access structure.

Keywords: multi-secret image sharing scheme, verifiable, de-tectable, general access structure

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Authors: Komal V. Aher, Sanjay B. Waykar

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Nowadays every individual having mobile device with them. In both computer vision and information retrieval Image search is currently hot topic with many applications. The proposed intelligent image search system is fully utilizing multimodal and multi-touch functionalities of smart phones which allows search with Image, Voice, and Text on mobile phones. The system will be more useful for users who already have pictures in their minds but have no proper descriptions or names to address them. The paper gives system with ability to form composite visual query to express user’s intention more clearly which helps to give more precise or appropriate results to user. The proposed algorithm will considerably get better in different aspects. System also uses Context based Image retrieval scheme to give significant outcomes. So system is able to achieve gain in terms of search performance, accuracy and user satisfaction.

Keywords: color space, histogram, mobile device, mobile visual search, multimodal search

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Authors: Hassan A. Alshahrani, Mehdi H. Hojjati

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In order to predict and model wrinkling which is caused by out of plane deformation due to compressive loading in the plane of the material during composite prepregs forming, it is necessary to quantitatively understand the relative magnitude of the bending stiffness. This study aims to examine the bending properties of out-of-autoclave (OOA) thermosetting prepreg under vertical cantilever test condition. A direct method for characterizing the bending behavior of composite prepregs was developed. The results from direct measurement were compared with results derived from an image-processing procedure that analyses the captured image during the vertical bending test. A numerical simulation was performed using ABAQUS to confirm the bending stiffness value.

Keywords: Bending stiffness, out-of-autoclave prepreg, forming process, numerical simulation.

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Authors: Mingxin Li, Liya Ni

Abstract:

Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

Procedia PDF Downloads 106

Authors: Jiankang Wang, Hongyang Yu

Abstract:

This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects.

Keywords: 3D reconstruction, bundlefusion, lossless compression, depth image

Procedia PDF Downloads 49