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

共 1469 条记录，以下是1271-1280 订阅

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Lossless compression of digital mammography using fixed block segmentation and pixel grouping

Lossless compression of digital mammography using fixed bloc...

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6th indian conference on computer vision, graphics and image processing, ICVGIP 2008

作者： Kumar, Ravi Koliwad, Shivaprakash Dwarakish, G.S. Department of IS and E. KVGCE Sullia Karnataka India Department of E and C. MCE Hassan Karnataka India Department of applied mechanics and hydraulics NITK Suratkal Karnataka India

ISBN: (纸本)9780769534763

A mammography is a specific type of imaging that uses low-dose x-ray system to examine breasts. This is an efficient means of early detection of breast cancer. High resolution is a common characteristic of such images. Archiving and retaining these data for at least three years is expensive, difficult and requires sophisticated data compression techniques. In this paper an efficient method is proposed for lossless compression of mammography images. After performing de-correlation of the image using two efficient predictors, the residue image is divided into 4x4 blocks. The blocks with all-zero pixels are identified using one bit code. Later, Second order of pixel grouping is employed to the remaining blocks to increase the coding efficiency. Such blocks are coded using Base offset method. Special techniques are used to save the header information. The method is tested using 25 mammograms from the MIAS database, each having a resolution of 1024x1024 pixels with 8 bits/pixel. Experimental results indicate better compression ratio when compared to JPEG 2000, JPEG-LS, PNG and JBIG. © 2008 IEEE.

关键词： image compression

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Semantic Event Detection and Classification in Cricket Video Sequence

Semantic Event Detection and Classification in Cricket Video...

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6th indian conference on computer vision, graphics and image processing

作者： Kolekar, M. H. Palaniappan, K. Sengupta, S. Univ Missouri Dept Comp Sci Columbia MO 65211 USA Indian Inst Technol Dept Elect & ECE Kharagpur W Bengal India

ISBN: (纸本)9781424442195

In this paper we present a novel hierarchical framework and effective algorithms for cricket event detection and classification. The proposed scheme performs a top-down video event detection and classification using hierarchical tree which avoids shot detection and clustering. In the hierarchy, at level-1, we use audio features, to extract excitement clips from the cricket video. At level-2, we classify excitement clips into real-time and replay segments. At level-3, we classify these segments into field view and non-field view based on dominant grass color ratio. At level-4a, we classify field view into pitch-view, long-view, and boundary view using motion-mask. At level-4b, we classify non-field view into close-up and crowd using edge density feature. At level-5a, we classify close-ups into the three frequently occurring classes batsman, bowler/fielder umpire using jersey color feature. At level-5b, we classify crowd segment into the two frequently occurring classes spectator and players' gathering using color feature. We show promising results, with correctly classified cricket events, enabling structural and temporal analysis, such as highlight extraction, and video skimming.

关键词： Semantics

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A Fourier Transform-based Approach to Fusion High Spatial Resolution Remote Sensing images

A Fourier Transform-based Approach to Fusion High Spatial Re...

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6th indian conference on computer vision, graphics and image processing

作者： Denipote, Juliana G. Paiva, Maria Stela V. Univ Sao Paulo EESC BR-05508 Sao Paulo Brazil

ISBN: (纸本)9781424442195

The modern remote sensing imaging sensors, like those in the IKONOS and QuickBird satellites, are capable of generating panchromatic images with one meter spatial resolution and multiespectral images with good spectral information. The principal objective of fusion in remote sensing is to obtain high-resolution multispectral images that can combine the spectral characteristic of the low-resolution multispectral images with the spatial information of the high-resolution panchromatic images. Traditional fusion methods, such as IHS, PCA and Brovey, can reach good spatial resolution results, but often cause spectral distortion problems. In the literature, it is possible to find some image fusion methods using frequency domain processing, like wavelet-based fusion methods. Although they preserve good spectral information, their spatial visual effects are not satisfactory. IHS fusion method enhanced by Fourier transform presents good spectral and spatial resolution results, but limits the number of spectral bands used in the fusion process to three. In this paper, a method based on Fourier transform is proposed in order to obtain good spatial and spectral resolutions, without limiting the number of bands. In order to compare the spatial and spectral effects of this new method with those of IHS, IHS enhanced by Fourier transform and wavelet-based methods, IKONOS panchromatic and multispectral images were used as the test data. Quantitative measurements such as correlation coefficient, discrepancy and Mean Structural Similarity index were applied to evaluate the quality of the fused images. The results have shown that the new method can keep almost the same spatial resolution as the panchromatic images, and its spectral effect is well preserved.

关键词： remote sensing IKONOS image fusion IHS wavelet transform Fourier transform frequency domain

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A Fuzzy approach to Region-of-interest coding in JPEG-2000 for ATR Applications from High Resolution Satellite images

A Fuzzy approach to Region-of-interest coding in JPEG-2000 f...

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6th indian conference on computer vision, graphics and image processing

作者： Raj, K. C. Emmanuel Sanjay Venkatraman, S. varadan, Geeta Systems Engineering Division Advanced Data Processing Research Institute(ADRIN) Dept. of Space. India

ISBN: (纸本)9781424442195

Automatic Target Recognition (ATR) from satellite imagery involves detection of Foreground (FG) objects from the Background (BG). ATR demands higher fidelity, which in turn requires more bitrate, hence a conventional compression, which does not discriminate targets with the background results in poor detection rate. Here we propose a mechanism to achieve lower bitrate without compromising the detection efficiency. By allowing the background to be coded with lower fidelity than the regions-of-interest (ROIs), significant gains can be achieved in terms of compression and hence in storage space and transmission times. One interesting feature of the new JPEG-2000 image coding standard is support of ROI coding using maximum shift (MaxShift) method, which allows for arbitrarily shaped ROI image compression without shape coding or explicitly transmitting any shape information to the decoder. We propose a Fuzzy C-Means clustering approach to generating arbitrary shape mask so as to cluster the images into regions of varying homogeneity. Homogenous ROIs can be coded at a lower bitrate than the high detail regions. This ensures that the target recognition process is not affected by the compression process. A validation benchmark using 'Fuzzy Feature Vectors' is proposed which checks the foreground objects for features like Rectangularity, Circularity. Elongatedness, Symmetry, Area etc., as compared to its uncompressed equivalent. The validation is done on Standard JPEG, JPEG-2000 with ROI coding and JPEG-2000 without ROI coding at preset bitrates and compared.

关键词： JPEG ROI JPEG-2000 Fuzzy Feature Vectors Object Profile Graphs

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Recognition of Multi-Oriented Touching Characters in Graphical Documents

Recognition of Multi-Oriented Touching Characters in Graphic...

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6th indian conference on computer vision, graphics and image processing

作者： Roy, Partha Pratim Pal, Umapada Llados, Josep Univ Autonoma Barcelona Comp Vis Ctr Bellaterra 08193 Spain Indian Stat Inst Comp Vision & Pattern Recognit Unit Kolkata India

ISBN: (纸本)9781424442195

Touching characters are major problem of achieving higher recognition rate in Optical Character Recognition (OCR). Present OCR systems do not perform well when adjacent characters touch. If characters are touched in graphical documents (e.g. map) then such touching string recognition is more difficult because in such documents touching characters appear in multi-oriented direction. In this paper, we present a scheme towards the recognition of English two-character multi-oriented touching strings. When two or more characters touch, the), generate a big cavity region at the background portion and we used this background information in our scheme. To handle the background information, convex hull is used. In this scheme, at first, a set of initial segmentation points is predicted based on the concave residues of the convex hull of the touching characters. Next, based on the initial points, we select some candidate segmentation lines. Finally the recognition confidence of two sub-images of a touching string, obtained from each candidate segmentation line is computed. The candidate segmentation line from which we get optimum confidence is the actual segmentation line and the corresponding characters in favour of which the two segmentation parts show optimum confidence is the recognition result of the touching string. To compute the recognition confidence, SVM classifier is used. The features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment we obtained encouraging result.

关键词： Optical character recognition

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A scalable projective bundle adjustment algorithm using the L norm

A scalable projective bundle adjustment algorithm using the ...

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6th indian conference on computer vision, graphics and image processing, ICVGIP 2008

作者： Mitra, Kaushik Chellappa, Rama Dept. of Electrical and Computer Engineering College Park MD United States

ISBN: (纸本)9780769534763

The traditional bundle adjustment algorithm for structure from motion problem has a computational complexity of O((m + n)3) per iteration and memory requirement of O(mn(m+n)), wheremis the number of cameras and n is the number of structure points. The sparse version of bundle adjustment has a computational complexity of O(m3+mn) per iteration and memory requirement of O(mn). Here we propose an algorithm that has a computational complexity of O(mn(vm + vn)) per iteration and memory requirement of O(max(m, n)). The proposed algorithm is based on minimizing the L norm of reprojection error. It alternately estimates the camera and structure parameters, thus reducing the potentially large scale optimization problem to many small scale subproblems each of which is a quasiconvex optimization problem and hence can be solved globally. Experiments using synthetic and real data show that the proposed algorithm gives good performance in terms of minimizing the reprojection error and also has a good convergence rate.© 2008 IEEE.

关键词： Computational complexity

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GA Based Neuro Fuzzy Techniques for Breast Cancer Identification

GA Based Neuro Fuzzy Techniques for Breast Cancer Identifica...

引用

International Machine vision and image processing conference

作者： Das, Arpita Bhattacharya, Mahua Univ Calcutta Inst Radio Phys & Elect 92 APC Rd Kolkata 700009 W Bengal India Indian Inst Informat Technol & Management Gwalior 474010 India

ISBN: (纸本)9780769533322

An intelligent computer-aided diagnostics system may be developed to assist the radiologists to recognize the masses / lesions appearing in breast in different groups of benignancy / malignancy. In present work we have attempted to develop a computer assisted treatment planning system implementing Genetic algorithm? based Neuro-fuzzy approaches. The boundary based features of the tumor lesions appearing in breast have been extracted for classification. The shape features represented by Fourier Descriptors, introduce a large number of feature vectors. Thus to classify different boundaries, a standard classifier needs a large number of inputs, and simultaneously to train the classifier a large number of training cycles are required This may invite the problem of over learning, followed by, chance of misclassification. In proposed Methodology, Genetic Algorithm (GA) has been used for searching of significant input feature vectors. Finally adaptive neuro fuzzy, based classifier has been introduced classification of tumor masses in breast.

关键词： Genetic algorithms

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Constraint Shortest Path Computation on Polyhedral Surfaces

Constraint Shortest Path Computation on Polyhedral Surfaces

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Synave Rémi Gueorguieva Stefka Desbarats Pascal UMR 5800 LaBRI Université Bordeaux 1 France

A new method to compute the shortest path over polyhedral surfaces is presented. Based on the consensus plane constrained subdivision of the initial surface, a discrete geodesic approximation is generated with respect... 详细信息

关键词： Shape Geophysics computing computer vision Surface reconstruction Strips Convergence computer graphics image processing Constraint optimization Robot motion

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Segmentation of Circular and Rectangular Shapes in an image Using Helmholtz Principle

Segmentation of Circular and Rectangular Shapes in an Image ...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Snehasis Mukherjee Dipti Prasad Mukherjee Indian Statistical Institute Electronics and Communication Sciences Unit Kolkata India

We propose algorithms to extract groups of meaningful image level lines using Helmholtz perception principle. In this paper, the meaningfulness refers to the segmentation of circular and rectangular shapes in an image. We propose an objective assessment of meaningfulness of an image level line when the level line takes the shape of circle or rectangular segment. We have shown that a logical threshold in the meaningfulness value segments images from a variety of applications.

关键词： image segmentation Shape Pixel Noise shaping computer vision White noise Layout computer graphics image processing Colored noise

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Unusual Activity Analysis Using Video Epitomes and pLSA

Unusual Activity Analysis Using Video Epitomes and pLSA

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Ayesha Choudhary Manish Pal Subhashis Banerjee Santanu Chaudhury Department of Computer Science and Engineering Indian Institute of Technology New Delhi India Department of Electrical Engineering Indian Institute of Technology New Delhi India

In this paper, we address the problem of unsupervised learning of usual patterns of activities in an area under surveillance and detecting deviant patterns. We use video epitomes for segmenting foreground objects from background and obtain an approximate shape, trajectory and temporal information in the form of space-time patches. We apply pLSA for finding correlations among these patches to learn usual activities in the scene. We also extend pLSA to classify a novel video as usual or unusual.

关键词： Shape Video compression Layout Surveillance Unsupervised learning image reconstruction computer vision computer graphics image processing image analysis

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