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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Dalmia, Nandita Okade, Manish Natl Inst Technol Rourkela Dept Elect & Commun Engn Rourkela 769008 India

ISBN: (纸本)9781450347532

The Double JPEG problem in image forensics has been gaining importance since it involves two compression cycles and there is a possibility of tampering having taken place after the first cycle thereby calling for accurate methods to detect and localize the introduced tamper. First quantization matrix estimation which basically retrieves the missing quantization table of the first cycle is one of the ways of image authentication for Double JPEG images. This paper presents a robust method for first quantization matrix estimation in case of double compressed JPEG images by improving the selection strategy which chooses the quantization estimate from the filtered DCT histograms. The selection strategy is made robust by increasing the available statistics utilizing the DCT coefficients from the double compressed image under investigation coupled with performing relative comparison between the obtained histograms followed by a novel priority assignment and selection step, which accurately estimates the first quantization value. Experimental testing and comparative analysis with two state-of-art methods show the robustness of the proposed method for accurate first quantization estimation. The proposed method finds its application in image forensics as well as in steganalysis.

关键词： image forensics double JPEG compression tampering histogram analysis prioritizedlists split noise

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Improving image decomposition method of the 3-MRC coding of scanned compound document images

Improving image decomposition method of the 3-MRC coding of ...

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

作者： Lakhani, Gopal Texas Tech Univ Lubbock TX 79424 USA

ISBN: (纸本)9781424442195

This paper discusses image decomposition problem of the 3-layer MRC model based coding of scanned (noisy) document images. A widely-used approach for document decomposition is to divide the document image into blocks and split the pixel histogram of each block into two halves by minimizing the sum of variance of its pixels with the mean of the halms. We propose to split a block by minimizing the variance of one half with its minimum pixel and the variance of the other half with its maximum pixel. Our goal is to increase the gap between the two halves by avoiding splitting of any cluster of pixels into both halves. It should help reduce complexity of the generated mask. Moreover, we do not decompose a block if it has no edge points, again to reduce the mask complexity. We also implement a noise reduction heuristic in the mask layer to correct placement of transition pixels. We provide simple analysis and evaluate block energy in terms of the DCT coefficients of the resulting FG/BG layer blocks. Experimental results show that code size of the mask layer of our test images, obtained using proposed processing is reduced to nearly half of the mask obtained by a straightforward 3-MRC implementation.

关键词： Document image coding Mixed raster content model mask noise reduction

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Fuzzy rule based document image segmentation for component labeling

Fuzzy rule based document image segmentation for component l...

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2011 3rd National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2011

作者： Kapoor, Aditi Pandey, Parul Biswas, K.K. Amar Nath and Shashi Khosla School of Information Technology Indian Institute of Technology Delhi Hauz Khas New Delhi - 110016 India Department of Computer Science and Engineering Indian Institute of Technology Delhi Hauz Khas New Delhi - 110016 India

ISBN: (纸本)9780769545998

In this paper, we propose a fuzzy rule based method for extensive segmentation of documents, with the view of labeling various components like page header, title, figure and tables, column divider, text etc. The fuzzy rules are learned using evolutionary computation, based on labeled document images serving as ground truth. The proposed fuzzy rules exploit the placement heuristics among the various components in a technical paper. A genetic algorithm involving individual fitness functions of all components selects the best set of rules. The effectiveness of the proposed method is validated through a case study involving 300 documents. It is also shown that this approach can be extended to segmentation of magazine pages. © 2011 IEEE.

关键词： Fuzzy rules

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On the view synthesis of man-made scenes using uncalibrated cameras

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PATTERN RECOGNITION LETTERS 2007年第3期28卷 384-393页

作者： Sharma, Geetika Chaudhury, Santanu Srivastava, J. B. Indian Inst Technol Dept Elect Engn New Delhi 110016 India Indian Inst Technol Dept Math New Delhi 110016 India

We have attempted the problem of novel view synthesis of scenes containing man-made objects from images taken by arbitrary, uncalibrated cameras. Under the assumption of availability of the correspondence of three vanishing points, in general position, we propose two techniques. The first is a transfer-based scheme which synthesizes new views with only a translation of the virtual camera and computes z-buffer values for handling occlusions in synthesized views. The second is a reconstruction-based scheme which synthesizes arbitrary new views in which the camera can undergo rotation as well as translation. We present experimental results to establish the validity of both formulations. (c) 2006 Published by Elsevier B.V.

关键词： image-based rendering novel view synthesis uncalibrated cameras

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Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

Learning Feature Trajectories Using Gabor Filter Bank for Hu...

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

作者： Gupta, Sunil Kumar Kumar, Y. Senthil Ramakrishnan, K. R. Indian Inst Sci Bangalore 12 Karnataka India

ISBN: (纸本)9781424442195

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using Dynamic Time Warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

关键词： Gabor filters

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A Novel Key-frame Detection Technique using Statistical Run Test and Majority Voting

A Novel Key-frame Detection Technique using Statistical Run ...

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

作者： Mohanta, P. P. Saha, S. K. Chanda, B. Indian Stat Inst ECS Unit Kolkata India Jadavpur Univ CSE Dept Kolkata India

ISBN: (纸本)9781424442195

Detection of representative frames, also called key-frames, is essential for efficient indexing, browsing and retrieval of video data and also for video summarization. Once a video stream is segmented into shots, the representative frames or key-frames for the shot are selected. The number of such frames in a shot may vary depending on the variation it? the content. Thus, for a wide variety of shots automatic selection of suitable number of representative frames still remains a challenge. In this work, we propose a novel scheme for key-frame detection by dividing an available shot into subshots using hypothesis testing and majority voting. Each subshot is supposed to be uniform in terms of visual content. Then for each subshot, the frame rendering the highest fidelity is extracted as the key-frame. Experimental result shows that the scheme works satisfactorily for a wide variety of shots.

关键词： Video recording

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Design and Implementation of a Robust Palm Biometrics Recognition and Verification System

Design and Implementation of a Robust Palm Biometrics Recogn...

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

作者： Parashar, Saurabh Vardhan, Anand Patvardhan, C. Kalra, Prem Kumar Dayalbagh Educ Inst Agra Uttar Pradesh India Indian Inst Technol Delhi India

ISBN: (纸本)9781424442195

Complete design and implementation of a robust palm biometrics recognition and verification system has been presented. The paper attempts to scientifically develop a comprehensive set of hand geometry features and develop an original algorithm from a fundamental level to robustly compute a selected set of features so as to minimize palm placement effect. These features are combined with chrominance features, to achieve recognition and verification accuracy, significant with respect to the current state in palm biometrics research. The algorithm has been kept robust, simple and computationally efficient while the implementation is relatively inexpensive. The experiments on recognition, Principal Components Analysis (PCA) and verification, on a dataset of 100 users strongly confirm the utility of robustly calculating a comprehensive set Of scientifically selected hand geometry features. The results uncover the potential of hand geometry features and confirm that the system can be used in medium to high security environments.

关键词： Biometrics

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Fragment Based Tracking for Scale and Orientation Adaptation

Fragment Based Tracking for Scale and Orientation Adaptation

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

作者： Srikrishnan, V. Nagaraj, T. Chaudhuri, Subhasis Indian Inst Technol Dept Elect Engn VIP Lab Bombay 400076 Maharashtra India

ISBN: (纸本)9781424442195

In this work, we propose a simple yet highly effective algorithm for tracking a target through significant scale and orientation change. We divide the target into a number of fragments and tracking of the whole target is achieved by coordinated tracking of the individual fragments. We use the mean shift algorithm to move the individual fragments to the nearest minima, though an), other method like integral histograms could also be used. In contrast to the other fragment based approaches, which fix the relative positions of fragments within the target, we permit the fragments to move freely within certain bounds. Furthermore, we use a constant velocity Kalman filter for two purposes. Firstly, Kalman filter achieves robust tracking because of usage of a motion model. Secondly, to maintain coherence amongst the fragments, we use a coupled state transition model for the Kalman filter Using the proposed tracking algorithm, we have experimented on several videos consisting of several hundred frames length each and obtained excellent results.

关键词： Kalman filters

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Iris recognition using partial sum of second order Taylor Series Expansion 16

Iris recognition using partial sum of second order Taylor Se...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Shekar, B. H. Bhat, Sharada S. Mangalore Univ Dept Comp Sci Mangalore Karnataka India Govt Arts & Sci Coll Karwar Karnataka India

ISBN: (纸本)9781450347532

Iris is presently one among the most sought after traits in biometric research. Extracting well-suited features from iris has been a favourite topic of the researchers. This paper proposes a novel iris feature extraction technique based on partial sum of second order Taylor series expansion (TSE). The finite sum of TSE computed on an arbitrary small neighbourhood on multiple scales can approximate the function extremely well and hence provides a powerful mechanism to extract the complex natured localised features of iris structure. To compute the higher order derivatives of TSE, we propose kernel structures by extending the Sobel operators. Extensive experiments are conducted with multiple scales on IITD, MMU v-2 and CASIA v-4 distance databases and comparative analysis is performed with the existing algorithms to substantiate the performance of the proposed method.

关键词： Taylor Series Expansion Iris Feature Extraction Iris Recognition Biometrics

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Depth Estimation from Single image using Machine Learning Techniques 16

Depth Estimation from Single Image using Machine Learning Te...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Chahal, Nidhi Pippal, Meghna Chaudhury, Santanu Indian Inst Technol Delhi India Cent Elect Engn Res Inst Pilani Pilani Rajasthan India

ISBN: (纸本)9781450347532

In this paper, the problem of depth estimation from single monocular image is considered. The depth cues such as motion, stereo correspondences are not present in single image which makes the task more challenging. We propose a machine learning based approach for extracting depth information from single image. The deep learning is used for extracting features, then, initial depths are generated using manifold learning in which neighborhood preserving embedding algorithm is used. Then, fixed point supervised learning is applied for sequential labeling to obtain more consistent and accurate depth maps. The features used are initial depths obtained from manifold learning and various image based features including texture, color and edges which provide useful information about depth. A fixed point contraction mapping function is generated using which depth map is predicted for new structured input image. The transfer learning approach is also used for improvement in learning in a new task through the transfer of knowledge from a related task that has already been learned. The predicted depth maps are reliable, accurate and very close to ground truth depths which is validated using objective measures: RMSE, PSNR, SSIM and subjective measure: MOS score.

关键词： Monocular manifold sequential labeling

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