This paper is aimed at exploring the potential of using discriminatory primitives containing words for the task of detecting skilled forgeries. We consider handwritten Devanagri documents for this work. We have obtain...
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ISBN:
(纸本)9781479915880
This paper is aimed at exploring the potential of using discriminatory primitives containing words for the task of detecting skilled forgeries. We consider handwritten Devanagri documents for this work. We have obtained experimental handwriting data from subjects who have contributed handwriting samples in their natural handwriting. Other authors are asked to imitate the writing style of the subjects to produce a skilled forgery sample. Most of the literature dealing with writer recognition focus on signatures and very few reports have addressed the problem of detecting forgeries for handwritten indian scripts. We also use multiple words based classification for the targeted task of forgery detection. Our experiments show encouraging results.
Large space with many cameras require huge storage and computational power to process these data for surveillance applications. In this paper we propose a distributed camera and processing based face detection and rec...
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ISBN:
(纸本)9781479915880
Large space with many cameras require huge storage and computational power to process these data for surveillance applications. In this paper we propose a distributed camera and processing based face detection and recognition system which can generate information for finding spatiotemporal movement pattern of individuals over a large monitored space. The system is built upon Hadoop Distributed File System using map reduce programming model. A novel key generation scheme using distance based hashing technique has been used for distribution of the face matching task. Experimental results have established effectiveness of the technique.
In this paper, we address the problem of separating the diffuse and specular reflection components of complex textured surfaces from a single color image. Unlike most previous approaches that assume accurate knowledge...
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ISBN:
(纸本)9781479915880
In this paper, we address the problem of separating the diffuse and specular reflection components of complex textured surfaces from a single color image. Unlike most previous approaches that assume accurate knowledge of illumination source color for this task, we analyze errors in source color information to perform robust separation. The analysis leads to a simple, efficient and robust algorithm to estimate the diffuse and specular components using the estimated source color. The algorithm is completely automatic and does not need explicit color segmentation or color boundary detection as required by many existing methods. Results on complex textured images show the effectiveness of the proposed algorithm for robust reflection component separation.
This paper presents a novel method for discovery and recognition of hairstyles in a collection of colored face images. We propose the use of Agglomerative clustering for automatic discovery of distinct hairstyles. Our...
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ISBN:
(纸本)9781479915880
This paper presents a novel method for discovery and recognition of hairstyles in a collection of colored face images. We propose the use of Agglomerative clustering for automatic discovery of distinct hairstyles. Our method proposes automated approach for generation of hair, background and face-skin probability-masks for different hairstyle category without requiring manual annotation. The probability-masks based density estimates are subsequently applied for recognizing the hairstyle in a new face image. The proposed methodology has been verified with a synthetic dataset of approximately thousand images, randomly collected from the Internet.
The video coding standard H.264 uses Contextbased Adaptive Variable Length Coding (CAVLC) as one of its entropy encoding techniques. This paper proposes VLSI architecture for CAVLC algorithm. The designed hardware mee...
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ISBN:
(纸本)9781479915880
The video coding standard H.264 uses Contextbased Adaptive Variable Length Coding (CAVLC) as one of its entropy encoding techniques. This paper proposes VLSI architecture for CAVLC algorithm. The designed hardware meets the required speed of H.264 without compromising the hardware cost. The CAVLC encoder works at a maximum clock frequency of 126 MHz when implemented in Xilinx 10.1i, Virtex-5 technology. The speed is quite appreciable when compared to other existing works. The implemented architecture meets the required rate for processing of HD-1080 format video sequence.
In this paper we have proposed methods for restoration of artifacts called Partial Color Artifact(PCA) and Blotches which appear frequently in old video films. The PCA occurs due to partial loss of information in the ...
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ISBN:
(纸本)9781479915880
In this paper we have proposed methods for restoration of artifacts called Partial Color Artifact(PCA) and Blotches which appear frequently in old video films. The PCA occurs due to partial loss of information in the upper color layers of the video film. As the inner most color layer is unaffected, the information present in this inner most color layer of the film aids in the reconstruction of damaged pixels from previously reconstructed frames. In Blotch artifact the pixel information is completely lost. The proposed Blotch reconstruction method is based on sparse recovery of signals from small number of measurements. Our blotch reconstruction process is computationally efficient because the image is segmented into non overlapping blocks and reconstruction is done block wise.
A Rough Set Theory based closed form object boundary detection method has been suggested in this paper. Most of the edge detection methods fail in getting closed boundary of objects of any shape present in the image. ...
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ISBN:
(纸本)9781479915880
A Rough Set Theory based closed form object boundary detection method has been suggested in this paper. Most of the edge detection methods fail in getting closed boundary of objects of any shape present in the image. Active contour based methods are available to get such object boundaries. The Multiphase Chan-Vese Active Contour Method is one of the most popular of such techniques. However, it is constrained with number of objects present in the image. The granular processing using Rough Set method overcomes this constraint and provides a closed curve around the boundary of the objects. This information can further be utilized in selection of similar patches for various imageprocessing problems such as image Denoising, image Super-resolution, image Segmentation etc. The proposed boundary detection method has been tested in presence of noise also. The experimental results have shown on synthetic image as well as on MRI of human brain. The performance of proposed method is found to be encouraging.
This paper proposes a novel framework that unifies the concept of sparsity of a signal over a properly chosen basis set and the theory of signal reconstruction via compressed sensing in order to obtain a high-resoluti...
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ISBN:
(纸本)9781479915880
This paper proposes a novel framework that unifies the concept of sparsity of a signal over a properly chosen basis set and the theory of signal reconstruction via compressed sensing in order to obtain a high-resolution image derived by using a single down-sampled version of the same image. First, we enforce sparse overcomplete representations on the low-resolution patches of the input image. Then, using the sparse coefficients as obtained above, we reconstruct a high-resolution output image. A blurring matrix is introduced in order to enhance the incoherency between the sparsifying dictionary and the sensing matrices which also resulted in better preservation of image edges and other textures. When compared with the similar techniques, the proposed method yields much better result both visually and quantitatively.
This paper presents the design of STAR (Spatio-Temporal Analysis and Retrieval), an unsupervised Content Based Video Retrieval (CBVR) System. STAR's key insight and primary contribution is that it models video con...
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ISBN:
(纸本)9781479915880
This paper presents the design of STAR (Spatio-Temporal Analysis and Retrieval), an unsupervised Content Based Video Retrieval (CBVR) System. STAR's key insight and primary contribution is that it models video content using a joint spatio-temporal feature representation and retrieves videos from the database which have similar moving object and trajectories of motion. Foreground moving blobs from a moving camera video shot are extracted, along with a trajectory for camera motion compensation, to form the space-time volume (STV). The STV is processed to obtain the EMST-CSS representation, which can discriminate across different categories of videos. Performance of STAR has been evaluated qualitatively and quantitatively using precision-recall metric on benchmark video datasets having unconstrained video shots, to exhibit efficiency of STAR.
In this paper, we propose a modified version of the standard proportional-derivative (PD) controller for biped locomotion. Our improvements stabilize the biped for high gain PD controllers. The main idea of our approa...
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ISBN:
(纸本)9781479915880
In this paper, we propose a modified version of the standard proportional-derivative (PD) controller for biped locomotion. Our improvements stabilize the biped for high gain PD controllers. The main idea of our approach involves applying corrective component to the existing framework, so that it prevents overshooting at high gains to stabilize the biped. We use pose control graphs to represent various gaits for the biped. We demonstrate with our improvements that the biped controller is stable while walking on irregular terrains. We also demonstrate that our formulation provides additional stability to the biped under minor impediments while in motion.
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