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检索条件"任意字段=Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing"

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Study of variation of pelvis positioning for patients suffering from rectal cancer using daily kilo-voltage cone beam CT images

Study of variation of pelvis positioning for patients suffer...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sayan Mandal Bijju Kranthi Veduruparthi Jayanta Mukherjee Partha Pratim Das Indranil Mallick Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Department of Radiation Oncology Tata Medical Center Kolkata

ISBN: (纸本)9781467385657

Radiation therapy is a standard treatment for a large variety of cancers. Radiation treatment planning involves delineating tumor, areas-at-risk, as well as normal anatomical structures. Automated techniques for detection and segmentation of tumor is a challenging task because of the absence of any standard model to identify anatomical structures. As radiation therapy is delivered in multiple daily doses (called fractions) - treatment fields need to be positioned so that the daily uncertainties in the target position are covered adequately. This is done by adding a margin called the Planning Target Volume (PTV) margin around the clinical target volume. The PTV margin is determined from an understanding of the daily uncertainties. In this paper, we intend to aid doctors in determining the uncertainties of daily pelvis positioning for radiotherapy by estimating the degree of change in the pelvic bone position. We propose a technique for automatically detecting regions of pelvic bone anatomy from CBCT images. We track the change in the bone positions in pelvic regions on a daily basis. A small change suggests that the uncertainty involved in the position of tumorous cell is less, indicating that the planning target margin may be reduced substantially.

关键词： Planning Computed tomography Pelvic bones Tumors Shape Correlation

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Writer Identification from offline isolated Bangla characters and numerals 13

Writer Identification from offline isolated Bangla character...

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13th International conference on Document Analysis and Recognition, ICDAR 2015

作者： Adak, Chandranath Chaudhuri, Bidyut B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9781479918058

Writer identification is an essential component in computational forensic. In this paper, we attempt to do this job based only on isolated characters and numerals. For that, at first, some points of interest (keypoints) on the image are detected by structural analysis and SIFT based detector. Then we calculate a set of features within a certain neighborhood of the keypoint and employ fusion rule on multiple probabilistic SVM classifiers output for writer identification. For experimental analysis, a database containing 212,300 isolated Bangla orthosyllabic characters and numerals are generated with the help of 100 writers. We obtain fairly good result to identify a writer. We also try to find a small set of highly discriminative characters storing extra information about the writing style of an individual. © 2015 IEEE.

关键词： handwriting recognition natural language processing probability support vector machines Bangla orthosyllabic characters SIFT based detector computational forensic isolated Bangla characters isolated Bangla numerals isolated characters multiple probabilistic SVM classifiers structural analysis writer identification Chlorine Discriminative Bangla character Handwriting analysis Writer identification Numerals handwriting recognition structural analysis Structural analysis Support Vector Network Natural Language processing Writers Chlorine

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Synthetic handwritten Odia numeral database: From shallow hundreds to comprehensive thousands

Synthetic handwritten Odia numeral database: From shallow hu...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Kalyan S Dash N B Puhan Ganapati Panda School of Electrical Sciences Indian Institute of Technology Bhubaneswar India

Comprehensive database that contains all possible variations of handwriting is crucial for training and recognition. The primary challenge for an optical character recognizer (OCR) is that a number of interclass characters bear structural resemblance whereas images within a class render much dissimilarity. Acquisition of such a large database that ensures robust training of the recognizer is a painstaking task. Therefore, recent research interests have been to create, from a few samples of handwriting, a comprehensive synthetic database which not only ensures naturalness, but provides much needed pattern variability. In this paper, we propose a new approach of synthetic handwritten numeral generation for Odia language using interclass deformation. We experimentally evaluate the generated databases using the state-of-the-art recognition systems. The recognition results are compared on two benchmark databases (ISI Kolkata and IIT Bhubaneswar Odia numeral) as well as two newly created synthetic databases. The Odia numeral database sizes are increased by 20-fold each using our proposed approach. The introduction of nonlinear pattern variance because of interclass deformation is proved to pose better challenge to conventional recognizers. We also experimented on a mixture of original and synthetic database for training the OCR to achieve robustness and higher accuracy.

关键词： Databases Handwriting recognition Training Shape Optical character recognition software Robustness

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Validation of stimulus for EEG signal based cognitive load analysis

Validation of stimulus for EEG signal based cognitive load a...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Aniruddha Sinha Debatri Chatterjee Sanjoy Kumar Saha Anupam Basu Innovation Lab Tata Consultancy Services Ltd. Kolkata India Computer Science & Engineering Jadavpur University Kolkata India Computer Science & Engineering Indian Institute of Technology Kharagpur India

Cognitive load is defined as the mental workload imparted on brain while doing a task. The amount of cognitive load experienced depends on individual's ability of perception, assimilation and response to a task. Real-time measurement of the level of cognitive load using low cost Electroencephalogram (EEG) signal enables understanding of personal cognitive skills. In this paper, we propose a methodology of selecting a reference task whose bio-markers closely match with a given task while probing different cognitive abilities. The benefit of this approach is to have a limited set of training models for the reference tasks related to various cognitive categories and use the same for a variety of unknown tasks. Experiment is performed for two levels of cognitive load with three different tasks namely Stroop color task, logical reasoning task and usage of on-screen keyboards. The training models of the reference tasks, selected by cluster analysis of low and high cognitive levels are used to evaluate an unknown task. Experimental results indicate that the Stroop is a better reference for On-Screen keyboard test compared to the Logical reasoning test. Support vector machine (SVM) and principal component analysis (PCA) followed by SVM (PCA-SVM) are used as the classifiers for the testing.

关键词： Electroencephalography Keyboards Layout Training Cognition Brain models

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Lip contour detection for estimation of mouth opening area

Lip contour detection for estimation of mouth opening area

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Shreyansh Jain Prem C. Pandey Rajbabu Velmurugan Department of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

In speech training aids for providing visual feedback of the articulatory efforts, time-varying vocal tract shape during speech production is generally obtained by linear prediction (LP) analysis of the speech signal and assuming a constant area at the glottis end as a reference. Its variation during speech production causes errors in the estimated vocal tract shape. The problem can be overcome by using area of the mouth opening as the reference. This area can be estimated by detecting the inner lip contour from the video recording of speaker's face during speech utterance. A technique for detection of inner lip contour, based on color transformation and template matching, is presented for reducing the errors caused by presence of teeth and tongue. Face detection by Viola-Jones algorithm, localization using a mouth detection technique, and outer lip contour detection are used to narrow down the search region for inner mouth opening. Presence of the teeth is masked by separate color transformations for upper and lower lip segments. For reducing the errors due to visibility of the tongue, which may not have any significant separation from the lips in the color space, a template matching technique is employed. It is used separately for the upper and lower lip segments to obtain the mouth opening area. The technique has been validated against graphically measured values of the mouth opening and found to be successful in estimating the mouth opening area, and it is not affected by skin hue and presence of teeth.

关键词： Teeth Estimation Speech Face Tongue Shape

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An IDE-agnostic system to capture reading behaviour of C++ programs using eye-gaze tracker

An IDE-agnostic system to capture reading behaviour of C++ p...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sayani Mondal Partha Pratim Das Rajendra Mishra School of Engineering Entrepreneurship Indian Institute of Technology Kharagpur India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India

ISBN: (纸本)9781467385657

Over 70% of software development effort is spent in software maintenance comprising bug fixes and version updates. These activities involve fast comprehension of large codebases authored by multiple developers. Developers are mostly trained to write code while in practice they often need to read code. Hence effective and efficient systems are needed to assess the code reading ability of developers. While there have been some studies on program comprehension, they do not deliver a working system. They use an IDE (Integrated Development Environment) that more suits the needs of program comprehension system and caters less to the needs of program development or developers. Importantly, to measure the productivity of a developer, we need to use the same IDE which the developer regularly uses and is comfortable with. In short, such systems need to be IDE-agnostic. In this paper, we build a front-end for a program comprehension assessment system using Tobii X2-30 eye-gaze tracker. The system comprises a flat screen monitor fitted with X2-30 and the developer seated within a specific distance from it. As the developer reads the C++ program, her eye movements are captured by X2-30 at 30 samples / sec. Once the reading is over, the X2-30 data stream is analysed off-line along with the program text to generate the reading sequence of the tokens as read by the developer. We use image analysis to extract regions from the displayed program text corresponding to token lexicons in C++. The lexical tokens are extracted separately from the program text. Finally we stitch the image regions, gaze points in and around the regions, and the tokens to generate the reading streams. We use several heuristics to compress the stream for semantic clarity. Several experiments have been conducted to estimate the accuracy of the generated sequences. In future, we plan to mine these reading sequences for extracting the comprehension features and develop metrics for reading skills.

关键词： Streaming media image segmentation Tracking Feature extraction Solids Semantics Visualization

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Psoriatic plaque segmentation in skin images

Psoriatic plaque segmentation in skin images

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Anabik Pal Utpal Garain Raghunath Chatterjee Swapan Senapati CVPRU ISI Kolkata West Bengal India Indian Statistical Institute Kolkata West Bengal IN (Consultant Dermatologist) Uttarpara Hooghly West Bengal India

This paper concerns about automatic psoriatic plaque segmentation in skin images. A novel pixel clustering based image segmentation approach is proposed. The clustering approach works with the circular-linear color spaces which remained unexplored because of the unavailability of appropriate mixture models and hence, the traditional clustering algorithms are incapable of handling such color spaces. This paper makes use of a novel Semi-Wrapped Gaussian Mixture Model (SWGMM) based approach for clustering image pixels. The experiment considers CIE Lch color space which is essentially a circular-linear space. The performance of SWGMM-based segmentation is compared to commonly used Fuzzy C-Means(FCM) and Fuzzy Kernel C-Means (FKCM)-based segmentation methods in linear color space. Results on a newly generated dataset show that SWGMM-based segmentation achieves accuracy of 82.84% in CIE Lch; whereas experiments with three linear color spaces namely, RGB, CIE L*u*v* and CIE L*a*b* show that FKCM and FCM achieve best accuracies of 78.80% and 77.79%, respectively in Lu*v* space. For comparing the clustering-based diseased detection result to a supervised pixel classification based approach, a support vector machines (SVM) based classifier is trained with labelled diseased and normal healthy skin pixels. As the number of images is limited for the present problem, SVM based diseased detection achieves 63.56% accuracy which is significantly lower than the accuracies given by the clustering based approaches.

关键词： image color analysis Skin Clustering algorithms image segmentation Kernel Support vector machines Colored noise

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Real time object tracking for high performance system using GPGPU

Real time object tracking for high performance system using ...

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International conference on Information processing (ICIP)

作者： Kinjal B. Mistree Ashutosh Dutt Shraddha V. Kothiya Department of Computer Engineering Chhotubhai Gopalbhai Patel Institute of Technology Bardoli India Indian Space Research Organization Ahmedabad India

ISBN: (纸本)9781467377591

Real time object tracking is the process of locating moving objects over time using the camera in video sequences in real time. The objective of object tracking is to associate target objects in consecutive video frames. Object tracking requires location and shape or features of objects in the video frames. Every tracking algorithm needs to detect moving object. So object detection is the preceding step of object tracking in computer vision applications. After that, detected object can be extracted by the feature of moving object to track that moving object into video scene. It is challenging task in image processing to track the objects into consecutive frames. Various challenges can arise due to complex object motion, irregular shape of object, occlusion of object to object and object to scene and real time processing requirements. Object tracking has a variety of uses, some of which are: surveillance and security, traffic monitoring, video communication, robot vision and animation.

关键词： Streaming media Object tracking Real-time systems Estimation graphics processing units Standards Central processing Unit

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FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL...

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IEEE International conference on image processing

作者： Kunal N. Chaudhury Department of Electrical Engineering Indian Institute of Science

ISBN: (纸本)9781479983407

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(σ~2) operations per pixel, where σ is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary σ (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the socalled Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.

关键词： Bilateral filter Approximation Gauss-polynomial Convolution Fast algorithm bilateral filters Convolution approximation Gauss pixel Filters Gaussian filtering Fasting Filtration Recursion Approximation algorithms

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Intelligent Computing and Applications: proceedings of the International conference on ICA, 22-24 December 2014 1

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丛书名： Advances in Intelligent Systems and Computing 343

2015年

作者： Durbadal Mandal, Rajib Kar, Swagatam Das, Bijaya Ketan Panigrahi (eds.)

ISBN: (数字)9788132222682

ISBN: (纸本)9788132222675;9788132222682

The idea of the 1st International conference on Intelligent Computing and Applications (ICICA 2014) is to bring the Research Engineers, Scientists, Industrialists, Scholars and Students together from in and around the globe to present the on-going research activities and hence to encourage research interactions between universities and industries. The conference provides opportunities for the delegates to exchange new ideas, applications and experiences, to establish research relations and to find global partners for future collaboration. The proceedings covers latest progresses in the cutting-edge research on various research areas of image, Language processing, computer vision and Pattern Recognition, Machine Learning, Data Mining and Computational Life Sciences, Management of Data including Big Data and Analytics, Distributed and Mobile Systems including Grid and Cloud infrastructure, Information Security and Privacy, VLSI, Electronic Circuits, Power Systems, Antenna, Computational fluid dynamics & Heat transfer, Intelligent Manufacturing, Signal processing, Intelligent Computing, Soft Computing, Bio-informatics, Bio Computing, Web Security, Privacy and E-Commerce, E-governance, Service Orient Architecture, Data Engineering, Open Systems, Optimization, Communications, Smart wireless and sensor Networks, Smart Antennae, Networking and Information security, Machine Learning, Mobile Computing and Applications, Industrial Automation and MES, Cloud Computing, Green IT, IT for Rural Engineering, Business Computing, Business Intelligence, ICT for Education for solving hard problems, and finally to create awareness about these domains to a wider audience of practitioners.

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