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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"

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Local Ternary Patterns and Maximum Bipartite Matching for Face Recognition

Local Ternary Patterns and Maximum Bipartite Matching for Fa...

引用

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

作者： Renuka Patnaik Raj Gupta Anurag Mittal Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai India

Local Binary Pattern (LBP) has been the successful feature descriptor used for face recognition. The basic idea in this method is to convert from an intensity space to an order space where the order of neighboring pixels is used to create a monotonic change illumination-invariant code for each point in the image. A drawback for this method, however, is that, in homogenous regions, the order of the pixel with respect to its neighbors is quite noisy. In this paper, we propose to use a third value which indicates if two pixels are similar in value. We also propose to match these patterns using maximum bipartite matching rather than histogram matching. Significant performance boost was found when compared to LBP and other standard methods like Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). We present our results on Extended Yale and FERET datasets.

关键词： Face recognition image edge detection Face Lighting Histograms Pattern matching

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Improving Video Stabilization in the Presence of Motion Blur

Improving Video Stabilization in the Presence of Motion Blur

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

作者： Manish Okade P.K. Biswas Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur India

In this paper we propose the idea of deblurring for efficient feature matching in the context of video stabilization. This is achieved by incorporating a motion deblurring block prior to the feature extraction and matching stage in the stabilization pipeline. The effect of motion blur on feature extraction and matching has not been investigated so far as most of the approaches have looked into deblurring as a post processing step. After preprocessing the blurred frames, the scale invariant feature transform points are used to find correspondence to get an estimate of the camera motion. Smoothing of the motion parameters to retain the desired motion is performed using a gaussian filter. Finally, inverse of the resulting image transform is carried out to obtain a stable video sequence. We compare our method to existing approaches and show how the inserted block improves the video stabilization performance. Interframe Transformation Fidelity (ITF) is used to show the superiority of our proposed approach.

关键词： Feature extraction Cameras Video sequences Motion estimation Indexes Motion compensation Pattern matching

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Statistical Video Tracking of Pomegranate Fruits

Statistical Video Tracking of Pomegranate Fruits

引用

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

作者： Ankush Roy Suvadeep Banerjee Debayan Roy Anupam Mukhopadhyay CVPR Unit Indian Statistical Institute Kolkata India Department of Electrical Engineering Jadavpur University Kolkata India

Efficient location of fruits in the trees is the most important criterion of an automatic robotic harvesting system. The main challenges faced in the development of the robotic harvesting arm are accurate identification of the fruits in dense foliages and detection of the occluded fruits. This paper proposes a statistical technique that accurately detects and tracks pomegranates in trees. A k-means clustering methodology is implemented as a preprocessor step followed by image analysis algorithms that finally locate the fruit accurately under varying conditions of illumination, human intervention, camera view etc. The simplicity of the technique is attributed to its real-time capability to detect and track fruits in a video of fruit-bearing trees. The ground truth data were computed on 25 video sequences and the system was tested on another 25 videos. The detection efficiency is as high as 96.3%.

关键词： image color analysis Cameras Robots Lighting Accuracy Streaming media Shape

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Video Compression Scheme Using DEMD Based Texture Synthesis

Video Compression Scheme Using DEMD Based Texture Synthesis

引用

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

作者： Mithilesh Kumar Jha Brejesh Lall Sumantra Dutta Roy Department of Electrical Engineering Indian Institute of Technology New Delhi India

In this paper we present a video coding scheme based on texture synthesis through Directional Empirical Mode Decomposition (DEMD). In this scheme P and B-frames of the video sequence are decomposed and parametrically coded with the help of DEMD algorithm, while I-frames are coded with the help of H.264. All P and B frames are decomposed into Intrinsic Mode Function (IMF) image and its residue. Only the first level IMF image for P and B frames are coded. At decoder stage subsequent IMF images are synthesized with the help of correlation search. Wavelet decomposition is performed over residual image and energy level at the HH band is used as a decision criterion for number of decomposition to be performed for optimum synthesis. The experimental result demonstrates the effectiveness of the algorithm in multi-resolution parametric modeling of image data which can be efficiently coded to achieve significant compression with acceptable quality. This scheme also enables to perform scalable coding of IMF parameters to achieve higher compression with perceptual quality.

关键词： image coding Video coding Video sequences Correlation Decoding Video compression image reconstruction

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Automatic Ear Detection for Online Biometric Applications

Automatic Ear Detection for Online Biometric Applications

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

作者： Amioy Kumar Madasu Hanmandlu Mohit Kuldeep H.M. Gupta Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India

The popularity of the ear biometrics is due to its unique distinct structure and high user convenience. However, the presence of hair and other skin attributes makes the automatic detection of ear contour a real challenge for online applications. This paper presents an online biometric authentication using ear contours acquired from a robust peg free acquisition set up. The Gaussian classifiers are used to first segment the skin and non-skin areas in the ear images. Laplacian of Gaussian is then used to compute edges of the skin areas, which helped to get ear-ROI images. A localized region based active contour is finally located in the ear-ROI images. The ear-contours are then employed for the authentication using log Gabor and SIFT features. The experimental results carried out on 700 ear images confirm the utility of the proposed approach.

关键词： Ear Feature extraction image edge detection Skin Authentication Databases Imaging

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Infinitesimal Machinery - A Nanorobotics System for Cancer Treatment

Infinitesimal Machinery - A Nanorobotics System for Cancer T...

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

作者： D. Dutta Majumder Sankar Karan Electronics and Communication Science Unit Indian Statistical Institute Kolkata India Institute of Radiophysics and Electronics Calcutta University Kolkata India

We present an approach to control the machines at the nano-meter or molecular scale (10-9 meter) in the perspective of the theory of cybernetics, the science of control, communication and computation with integration to complex man -- machines systems. Though our theory is general, on study we concentrate on nano-robot design and control by describing various molecular level systems. We discuss the method of special autonomous robotic systems that can be used for bio-medical and bio-mechanical purposes. We also present a theory of nano scale self assembly for prototyping bio-nano systems with the goal of implementing their internal optimum movements in biological environment to perform manipulation of nano-medicine specially for cancer treatment. The system casualty, state notation and automata for nano-robotic systems in the light of general systems theory are suggested.

关键词： Nanobioscience Cancer Shape Drugs Self-assembly Nanoparticles Cybernetics

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Parallelizing connectivity-based image processing operators in a multi-core environment

Parallelizing connectivity-based image processing operators ...

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International conference on Communications and Signal processing

作者： B Ravi Kiran K P Anoop Y Senthil Kumar CVAI Lab Indian Institute of Science Electrical Engineering Bangalore India Texas Instruments India Imaging Group Automotive Computer Vision group Bangalore India

With increasing computational requirements for state-of-art computer vision and graphics algorithms, multi-core processor implementations have picked up momentum. Adapting single core image processing algorithms for multi-core environment is difficult. Different platforms require a hand tailored approach to optimally fit the algorithm into a given multi-core architecture. An automatic compiler which could split and compile the code for any platform is desirable. Such a compiler doesn't exist and this kind of automation is tough to achieve. To aid existing compilers, we propose a simple software architecture framework for multi-core systems that aims to provide a uniform, scalable, and portable solution, solving specifically for connectivity based image processing operators.

关键词： image resolution Multicore processing graphics processing unit Hardware Encoding Labeling

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Summarization of Neonatal Video EEG for Seizure and Artifact Detection

Summarization of Neonatal Video EEG for Seizure and Artifact...

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

作者： Sourya Bhattacharyya Aditi Roy Debi Prosad Dogra Arunava Biswas Jayanta Mukherjee Arun Kumar Majumdar Bandana Majumdar Suchandra Mukherjee Arun Kumar Singh Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal India School of Information Technology Indian Institute of Technology Kharagpur West Bengal India Department of Neonatology IPGMER SSKM Hospital Kolkata West Bengal India

Monitoring neonatal EEG signal is useful in identifying neonatal convulsions or seizures. For neonates, seizures can be electrographic, electro clinical, or both simultaneously. Electrographic seizure is identified via recorded EEG signal, while electro clinical seizures exhibit clinical manifestations. Sometimes neonates can exhibit silent seizures which may be clinically invisible but identifiable in recorded EEG, or vice versa. Thus, simultaneous monitoring of video and recorded EEG determines the correlation between the electrographic and electro clinical seizures. Furthermore, analyzing the movements of the neonates can identify movement artifacts easily, thus preventing false seizure detection. However, storage of high quality video recordings require large storage space. As neonates do not commonly exhibit movements, summarizing the video for storing only patient movements along with corresponding timestamps, can be useful. In this paper, a video summarization method is proposed for efficient browsing of video-EEG. Identification and analysis of the patterns of interest is possible via summarized information, thus reducing effective analysis time. In addition, quantitative demonstration of electrographic and electro clinical seizures is presented to analyze the utility of video-EEG.

关键词： Electroencephalography Pediatrics Monitoring Electrodes Correlation Hospitals

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Off-line signature identification using background and foreground information

Off-line signature identification using background and foreg...

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2011 International conference on Digital image Computing: Techniques and Applications, DICTA 2011

作者： Pal, Srikanta Alireza, Alaei Pal, Umapada Blumenstein, Michael School of Information and Communication Technology Griffith University Gold Coast QLD Australia Department of Studies in Computer Science University of Mysore Mysore 570 006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9780769545882

Biometric systems play an important role in the field of information security as they are extremely required for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is currently receiving renewed interest and is only one of several techniques used to verify the identities of individuals. Signatures provide a secure means for confirmation and authorization in legal documents. So nowadays, signature identification and verification becomes an essential component in automating the rapid processing of documents containing embedded signatures. In this paper, a technique for a bi-script off-line signature identification system is proposed. In the proposed signature identification system, the signatures of English and Bengali (Bangla) are considered for the identification process. Different features such as under sampled bitmaps, modified chain-code direction features and gradient features computed from both background and foreground components are employed for this purpose. Support Vector Machines (SVMs) and Nearest Neighbour (NN) techniques are considered as classifiers for signature identification in the proposed system. A database of 1554 English signatures and 1092 Bengali signatures are used to generate the experimental results. Various results based on different features are calculated and analysed. The highest accuracies of 99.41%, 98.45%;and 97.75% are obtained based on the modified chain-code direction, under-sampled bitmaps and gradient features respectively using 1800 (1100 English+700 Bengali) samples for training and 846 (454 English+392 Bengali) samples for testing. © 2011 IEEE.

关键词： Biometrics

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Off-line Signature Identification Using Background and Foreground Information

Off-line Signature Identification Using Background and Foreg...

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proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Srikanta Pal Alaei Alireza Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Gold Coast Australia Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Biometric systems play an important role in the field of information security as they are extremely required for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is currently receiving renewed interest and is only one of several techniques used to verify the identities of individuals. Signatures provide a secure means for confirmation and authorization in legal documents. So nowadays, signature identification and verification becomes an essential component in automating the rapid processing of documents containing embedded signatures. In this paper, a technique for a bi-script off-line signature identification system is proposed. In the proposed signature identification system, the signatures of English and Bengali (Bangla) are considered for the identification process. Different features such as under sampled bitmaps, modified chain-code direction features and gradient features computed from both background and foreground components are employed for this purpose. Support Vector Machines (SVMs) and Nearest Neighbour (NN) techniques are considered as classifiers for signature identification in the proposed system. A database of 1554 English signatures and 1092 Bengali signatures are used to generate the experimental results. Various results based on different features are calculated and analysed. The highest accuracies of 99.41%, 98.45% and 97.75% are obtained based on the modified chain-code direction, under-sampled bitmaps and gradient features respectively using 1800 (1100 English+700 Bengali) samples for training and 846 (454 English+392 Bengali) samples for testing.

关键词： Feature extraction Support vector machines Handwriting recognition Training Educational institutions Kernel Databases

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