Search results for: Image transformations.
954 Fundamental Groups in Chaotic Flat Space and Its Retractions
Authors: A. E. El-Ahmady, M. Abu-Saleem
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The purpose of this paper is to give a combinatorial characterization and construct representations of the chaotic fundamental groups of the chaotic submanifolds of chaotic flat space by using some geometrical transformations. The chaotic homotopy groups of the limit folding for chaotic flat space are presented. The chaotic fundamental groups of some types of chaotic geodesics in chaotic flat space are deduced.
Keywords: Chaotic flat space, Chaotic folding, Chaotic retractions, Chaotic fundamental groups.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1529953 An Implementation of Stipple Operations
Authors: Nakhoon Baek
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Stipples are desired for pattern fillings and transparency effects. In contrast, some graphics standards, including OpenGL ES 1.1 and 2.0, omitted this feature. We represent details of providing line stipples and polygon stipples, through combining texture mapping and alpha blending functions. We start from the OpenGL-specified stipple-related API functions. The details of mathematical transformations are explained to get the correct texture coordinates. Then, the overall algorithm is represented, and its implementation results are followed. We accomplished both of line and polygon stipples, and verified its result with conformance test routines.Keywords: Stipple operation, OpenGL ES, Implementation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3080952 Advanced Image Analysis Tools Development for the Early Stage Bronchial Cancer Detection
Authors: P. Bountris, E. Farantatos, N. Apostolou
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Autofluorescence (AF) bronchoscopy is an established method to detect dysplasia and carcinoma in situ (CIS). For this reason the “Sotiria" Hospital uses the Karl Storz D-light system. However, in early tumor stages the visualization is not that obvious. With the help of a PC, we analyzed the color images we captured by developing certain tools in Matlab®. We used statistical methods based on texture analysis, signal processing methods based on Gabor models and conversion algorithms between devicedependent color spaces. Our belief is that we reduced the error made by the naked eye. The tools we implemented improve the quality of patients' life.Keywords: Bronchoscopy, digital image processing, lung cancer, texture analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1431951 Determinants of Brand Equity: Offering a Model to Chocolate Industry
Authors: Emari Hossien
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This study examined the underlying dimensions of brand equity in the chocolate industry. For this purpose, researchers developed a model to identify which factors are influential in building brand equity. The second purpose was to assess brand loyalty and brand images mediating effect between brand attitude, brand personality, brand association with brand equity. The study employed structural equation modeling to investigate the causal relationships between the dimensions of brand equity and brand equity itself. It specifically measured the way in which consumers’ perceptions of the dimensions of brand equity affected the overall brand equity evaluations. Data were collected from a sample of consumers of chocolate industry in Iran. The results of this empirical study indicate that brand loyalty and brand image are important components of brand equity in this industry. Moreover, the role of brand loyalty and brand image as mediating factors in the intention of brand equity are supported. The principal contribution of the present research is that it provides empirical evidence of the multidimensionality of consumer based brand equity, supporting Aaker´s and Keller´s conceptualization of brand equity. The present research also enriched brand equity building by incorporating the brand personality and brand image, as recommended by previous researchers. Moreover, creating the brand equity index in chocolate industry of Iran particularly is novel.Keywords: brand equity, brand personality, structural equationmodeling, Iran.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3613950 Toward Indoor and Outdoor Surveillance Using an Improved Fast Background Subtraction Algorithm
Authors: A. El Harraj, N. Raissouni
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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.
Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2084949 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line
Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez
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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.Keywords: Deep-learning, image classification, image identification, industrial engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 756948 Depth Estimation in DNN Using Stereo Thermal Image Pairs
Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge
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Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.
Keywords: thermal stereo matching, depth estimation, deep neural networks, CNN
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 693947 Performance of Compound Enhancement Algorithms on Dental Radiograph Images
Authors: S.A.Ahmad, M.N.Taib, N.E.A.Khalid, R.Ahmad, H.Taib
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The purpose of this research is to compare the original intra-oral digital dental radiograph images with images that are enhanced using a combination of image processing algorithms. Intraoral digital dental radiograph images are often noisy, blur edges and low in contrast. A combination of sharpening and enhancement method are used to overcome these problems. Three types of proposed compound algorithms used are Sharp Adaptive Histogram Equalization (SAHE), Sharp Median Adaptive Histogram Equalization (SMAHE) and Sharp Contrast adaptive histogram equalization (SCLAHE). This paper presents an initial study of the perception of six dentists on the details of abnormal pathologies and improvement of image quality in ten intra-oral radiographs. The research focus on the detection of only three types of pathology which is periapical radiolucency, widen periodontal ligament space and loss of lamina dura. The overall result shows that SCLAHE-s slightly improve the appearance of dental abnormalities- over the original image and also outperform the other two proposed compound algorithms.Keywords: intra-oral dental radiograph, histogram equalization, sharpening, CLAHE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1782946 Visual Search Based Indoor Localization in Low Light via RGB-D Camera
Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng
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Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.Keywords: Indoor navigation, low light, RGB-D camera, vision based.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1674945 Fully Automated Methods for the Detection and Segmentation of Mitochondria in Microscopy Images
Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn
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The detection and segmentation of mitochondria from fluorescence microscopy is crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. Although there exists a number of open-source software tools and artificial intelligence (AI) methods designed for analyzing mitochondrial images, the availability of only a few combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compactibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source Python and OpenCV library, the algorithms are implemented in three stages: pre-processing; image binarization; and coarse-to-fine segmentation. The proposed model is validated using the fluorescence mitochondrial dataset. Ground truth labels generated using Labkit were also used to evaluate the performance of our detection and segmentation model using precision, recall and rand index. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks concludes the paper.
Keywords: 2D, Binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 464944 On the Construction of Lightweight Circulant Maximum Distance Separable Matrices
Authors: Qinyi Mei, Li-Ping Wang
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MDS matrices are of great significance in the design of block ciphers and hash functions. In the present paper, we investigate the problem of constructing MDS matrices which are both lightweight and low-latency. We propose a new method of constructing lightweight MDS matrices using circulant matrices which can be implemented efficiently in hardware. Furthermore, we provide circulant MDS matrices with as few bit XOR operations as possible for the classical dimensions 4 × 4, 8 × 8 over the space of linear transformations over finite field F42 . In contrast to previous constructions of MDS matrices, our constructions have achieved fewer XORs.Keywords: Linear diffusion layer, circulant matrix, lightweight, MDS matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 852943 A Comparative Study of Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) for Airflow Measurement
Authors: Sijie Fu, Pascal-Henry Biwolé, Christian Mathis
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Among modern airflow measurement methods, Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV), as visualized and non-instructive measurement techniques, are playing more important role. This paper conducts a comparative experimental study for airflow measurement employing both techniques with the same condition. Velocity vector fields, velocity contour fields, voticity profiles and turbulence profiles are selected as the comparison indexes. The results show that the performance of both PIV and PTV techniques for airflow measurement is satisfied, but some differences between the both techniques are existed, it suggests that selecting the measurement technique should be based on a comprehensive consideration.
Keywords: PIV, PTV, airflow measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4306942 Robust Face Recognition Using Eigen Faces and Karhunen-Loeve Algorithm
Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Prateek Gupta
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The current research paper is an implementation of Eigen Faces and Karhunen-Loeve Algorithm for face recognition. The designed program works in a manner where a unique identification number is given to each face under trial. These faces are kept in a database from where any particular face can be matched and found out of the available test faces. The Karhunen –Loeve Algorithm has been implemented to find out the appropriate right face (with same features) with respect to given input image as test data image having unique identification number. The procedure involves usage of Eigen faces for the recognition of faces.Keywords: Eigen Faces, Karhunen-Loeve Algorithm, FaceRecognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1737941 The Invariant Properties of Two-Port Circuits
Authors: Alexandr A. Penin
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Application of projective geometry to the theory of two-ports and cascade circuits with a load change is considered. The equations linking the input and output of a two-port are interpreted as projective transformations which have the invariant as a cross-ratio of four points. This invariant has place for all regime parameters in all parts of a cascade circuit. This approach allows justifying the definition of a regime and its change, to calculate a circuit without explicitly finding the aparameters, to transmit accurately an analogue signal through the unstable two-port.
Keywords: Circuit regime, geometric circuit theory, projective geometry, two-port.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1568940 Non-destructive Watermelon Ripeness Determination Using Image Processing and Artificial Neural Network (ANN)
Authors: Shah Rizam M. S. B., Farah Yasmin A.R., Ahmad Ihsan M. Y., Shazana K.
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Agriculture products are being more demanding in market today. To increase its productivity, automation to produce these products will be very helpful. The purpose of this work is to measure and determine the ripeness and quality of watermelon. The textures on watermelon skin will be captured using digital camera. These images will be filtered using image processing technique. All these information gathered will be trained using ANN to determine the watermelon ripeness accuracy. Initial results showed that the best model has produced percentage accuracy of 86.51%, when measured at 32 hidden units with a balanced percentage rate of training dataset.Keywords: Artificial Neural Network (ANN), Digital ImageProcessing, YCbCr Colour Space, Watermelon Ripeness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2951939 Iris Recognition Based On the Low Order Norms of Gradient Components
Authors: Iman A. Saad, Loay E. George
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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.
Keywords: Iris recognition, contrast stretching, gradient features, texture features, Euclidean metric.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1964938 Fast Algorithm of Infrared Point Target Detection in Fluctuant Background
Authors: Yang Weiping, Zhang Zhilong, Li Jicheng, Chen Zengping, He Jun
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The background estimation approach using a small window median filter is presented on the bases of analyzing IR point target, noise and clutter model. After simplifying the two-dimensional filter, a simple method of adopting one-dimensional median filter is illustrated to make estimations of background according to the characteristics of IR scanning system. The adaptive threshold is used to segment canceled image in the background. Experimental results show that the algorithm achieved good performance and satisfy the requirement of big size image-s real-time processing.Keywords: Point target, background estimation, median filter, adaptive threshold, target detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1842937 Performance Analysis of Search Medical Imaging Service on Cloud Storage Using Decision Trees
Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel
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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.
Keywords: Cloud storage, decision trees, diagnostic image, search, telemedicine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 947936 Detection of Leaks in Water Mains Using Ground Penetrating Radar
Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi
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Ground Penetrating Radar (GPR) is one of the most effective electromagnetic techniques for non-destructive non-invasive subsurface features investigation. Water leak from pipelines is the most common undesirable reason of potable water losses. Rapid detection of such losses is going to enhance the use of the Water Distribution Networks (WDN) and decrease threatens associated with water mains leaks. In this study, GPR approach was developed to detect leaks by implementing an appropriate imaging analyzing strategy based on image refinement, reflection polarity and reflection amplitude that would ease the process of interpreting the collected raw radargram image.Keywords: Water Networks, Leakage, Water pipelines, Ground Penetrating Radar.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2314935 Effect of Implementation of Nonlinear Sequence Transformations on Power Series Expansion for a Class of Non-Linear Abel Equations
Authors: Javad Abdalkhani
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Convergence of power series solutions for a class of non-linear Abel type equations, including an equation that arises in nonlinear cooling of semi-infinite rods, is very slow inside their small radius of convergence. Beyond that the corresponding power series are wildly divergent. Implementation of nonlinear sequence transformation allow effortless evaluation of these power series on very large intervals..Keywords: Nonlinear transformation, Abel Volterra Equations, Mathematica
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1304934 A Self Configuring System for Object Recognition in Color Images
Authors: Michela Lecca
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System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a highly user-friendly tool.
Keywords: Automatic object recognition, clustering, content based image retrieval system, image segmentation, region adjacency graph, region grouping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1407933 Equivalent Transformation for Heterogeneous Traffic Cellular Automata
Authors: Shih-Ching Lo
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Understanding driving behavior is a complicated researching topic. To describe accurate speed, flow and density of a multiclass users traffic flow, an adequate model is needed. In this study, we propose the concept of standard passenger car equivalent (SPCE) instead of passenger car equivalent (PCE) to estimate the influence of heavy vehicles and slow cars. Traffic cellular automata model is employed to calibrate and validate the results. According to the simulated results, the SPCE transformations present good accuracy.Keywords: traffic flow, passenger car equivalent, cellular automata
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1709932 Random Subspace Neural Classifier for Meteor Recognition in the Night Sky
Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio
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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.
Keywords: Contour orientation histogram, meteors, night sky, RSC neural classifier, stars.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 405931 Robust Digital Cinema Watermarking
Authors: Sadi Vural, Hiromi Tomii, Hironori Yamauchi
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With the advent of digital cinema and digital broadcasting, copyright protection of video data has been one of the most important issues. We present a novel method of watermarking for video image data based on the hardware and digital wavelet transform techniques and name it as “traceable watermarking" because the watermarked data is constructed before the transmission process and traced after it has been received by an authorized user. In our method, we embed the watermark to the lowest part of each image frame in decoded video by using a hardware LSI. Digital Cinema is an important application for traceable watermarking since digital cinema system makes use of watermarking technology during content encoding, encryption, transmission, decoding and all the intermediate process to be done in digital cinema systems. The watermark is embedded into the randomly selected movie frames using hash functions. Embedded watermark information can be extracted from the decoded video data. For that, there is no need to access original movie data. Our experimental results show that proposed traceable watermarking method for digital cinema system is much better than the convenient watermarking techniques in terms of robustness, image quality, speed, simplicity and robust structure.Keywords: Decoder, Digital content, JPEG2000 Frame, System-On-Chip, traceable watermark, Hash Function, CRC-32.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1646930 Edge Detection Algorithm Based on Wavelet De-nosing Applied tothe X-ray Image Enhancement of the Electric Equipment
Authors: Fei Xue, Hong Yu, Da-da Wang, Wei Zhang, Rong-min Zou, Xiao-lanCai
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The X-ray technology has been used in non-destructive evaluation in the Power System, in which a visual non-destructive inspection method for the electrical equipment is provided. However, lots of noise is existed in the images that are got from the X-ray digital images equipment. Therefore, the auto defect detection which based on these images will be very difficult to proceed. A theory on X-ray image de-noising algorithm based on wavelet transform is proposed in this paper. Then the edge detection algorithm is used so that the defect can be pushed out. The result of experiment shows that the method which utilized by this paper is very useful for de-noising on the X-ray images.
Keywords: de-noising, edge detection, wavelet transform, X-ray
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1548929 Using Secure-Image Mechanism to Protect Mobile Agent Against Malicious Hosts
Authors: Tarig Mohamed Ahmed
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The usage of internet is rapidly increasing and the usage of mobile agent technology in internet environment has a great demand. The security issue one of main obstacles that restrict the mobile agent technology to spread. This paper proposes Secure-Image Mechanism (SIM) as a new mechanism to protect mobile agents against malicious hosts. . SIM aims to protect mobile agent by using the symmetric encryption and hash function in cryptography science. This mechanism can prevent the eavesdropping and alteration attacks. It assists the mobile agents to continue their journey normally incase attacks occurred.
Keywords: Agent protection, cryptography, mobile agent security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915928 Urban Land Cover Change of Olomouc City Using LANDSAT Images
Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula
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This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.
Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1829927 Efficient Lossless Compression of Weather Radar Data
Authors: Wei-hua Ai, Wei Yan, Xiang Li
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Data compression is used operationally to reduce bandwidth and storage requirements. An efficient method for achieving lossless weather radar data compression is presented. The characteristics of the data are taken into account and the optical linear prediction is used for the PPI images in the weather radar data in the proposed method. The next PPI image is identical to the current one and a dramatic reduction in source entropy is achieved by using the prediction algorithm. Some lossless compression methods are used to compress the predicted data. Experimental results show that for the weather radar data, the method proposed in this paper outperforms the other methods.
Keywords: Lossless compression, weather radar data, optical linear prediction, PPI image
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2256926 A CT-based Monte Carlo Dose Calculations for Proton Therapy Using a New Interface Program
Authors: A. Esmaili Torshabi, A. Terakawa, K. Ishii, H. Yamazaki, S. Matsuyama, Y. Kikuchi, M. Nakhostin, H. Sabet, A. Ishizaki, W. Yamashita, T. Togashi, J. Arikawa, H. Akiyama, K. Koyata
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The purpose of this study is to introduce a new interface program to calculate a dose distribution with Monte Carlo method in complex heterogeneous systems such as organs or tissues in proton therapy. This interface program was developed under MATLAB software and includes a friendly graphical user interface with several tools such as image properties adjustment or results display. Quadtree decomposition technique was used as an image segmentation algorithm to create optimum geometries from Computed Tomography (CT) images for dose calculations of proton beam. The result of the mentioned technique is a number of nonoverlapped squares with different sizes in every image. By this way the resolution of image segmentation is high enough in and near heterogeneous areas to preserve the precision of dose calculations and is low enough in homogeneous areas to reduce the number of cells directly. Furthermore a cell reduction algorithm can be used to combine neighboring cells with the same material. The validation of this method has been done in two ways; first, in comparison with experimental data obtained with 80 MeV proton beam in Cyclotron and Radioisotope Center (CYRIC) in Tohoku University and second, in comparison with data based on polybinary tissue calibration method, performed in CYRIC. These results are presented in this paper. This program can read the output file of Monte Carlo code while region of interest is selected manually, and give a plot of dose distribution of proton beam superimposed onto the CT images.Keywords: Monte Carlo, CT images, Quadtree decomposition, Interface program, Proton beam
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1866925 Optimized Vector Quantization for Bayer Color Filter Array
Authors: M. Lakshmi, J. Senthil Kumar
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Digital cameras to reduce cost, use an image sensor to capture color images. Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking. Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy. This paper proposes a new Vector Quantization (VQ) technique to construct a VQ codebook with Differential Evolution (DE) Algorithm. The new technique is compared to conventional Linde- Buzo-Gray (LBG) method.Keywords: Color Filter Array (CFA), Biorthogonal Wavelet, Vector Quantization (VQ), Differential Evolution (DE).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1905