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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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Off-line skilled forgery detection on handwritten Devanagri script

Off-line skilled forgery detection on handwritten Devanagri ...

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

作者： Nivedita Yadav Santanu Chaudhury Prem Kalra Amarnath and Shashi Khosla School of IT Indian Institute of Technology Delhi India Dept of Electrical Engineering Indian Institute of Technology Delhi India Dept of Computer Science and Engineering Indian Institute of Technology Delhi India

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.

关键词： Forgery Shape Feature extraction Histograms Forensics Accuracy Writing

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Perceptual video hashing based on the Achlioptas's random projections

Perceptual video hashing based on the Achlioptas's random pr...

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

作者： Sandeep R. Prabin K. Bora Department of EEE Indian Institute of Technology Guwahati Guwahati India

A perceptual video hashing function maps the perceptual content of a video into a fixed-length binary string called the perceptual hash. Perceptual hashing is a promising solution to the content-identification and the content-authentication problems. The projections of image and video data onto a subspace have been exploited in the literature to get a compact hash function. We propose a new perceptual video hashing algorithm based on the Achlioptas's random projections. Simulation results show that the proposed perceptual hash function is robust to common signal and image processing attacks.

关键词： Robustness Vectors Signal processing algorithms image processing Approximation algorithms Algorithm design and analysis Video sequences

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image deblurring in super-resolution framework

Image deblurring in super-resolution framework

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

作者： Srimanta Mandal Anil Kumar Sao School of Computing and Electrical Engineering Indian Institute of Technology Mandi India

In all image processing applications, it is important to extract the appropriate information from an image. But often the captured image is not clear enough to give the required information due to the imaging environment. Thus, it is essential to enhance the clarity of the image by some post-processing techniques. image deblurring is one of such techniques to remove the blurry effect of the captured image. This paper looks into this problem in a different way, where the deblurring of an image is addressed by solving image super-resolution problem. The blurred image is first down-sampled and then it is fed to the super-resolution framework to produce the deblurred high resolution image. In addition, the proposed approach states the requirement of edge preservation in the problem. The experimental results are comparable with the existing image deblurring algorithms.

关键词： PSNR image resolution image edge detection Boats Data mining Deconvolution Interpolation

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Partial Fourier reconstruction using subspace projection

Partial Fourier reconstruction using subspace projection

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

作者： Uma K. Kesavadas Chandrasekharan Joseph Suresh Paul Indian Institute of Information Technology and Management-Kerala Trivandrum Sree Chitra Tirunal Institute for Medical Science and Technology Trivandrum

Scan time reduction in MRI can be achieved by partial k-space reconstruction. Truncation of the k-space results in generation of artifacts in the reconstructed image. A subspace projection algorithm is developed for artifact-free reconstruction of sparse MRI. The algorithm is applied to a frequency weighted k-space, which fits into a signal-space model for sparse MR images. The application is illustrated using Magnetic Resonance Angiogram (MRA).

关键词： image reconstruction Vectors Magnetic resonance imaging Reconstruction algorithms Filling Magnetic resonance Noise

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OD-Match: PatchMatch based Optic Disk detection

OD-Match: PatchMatch based Optic Disk detection

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

作者： S. Avinash Ramakanth R. Venkatesh Babu SERC Indian Institute of Science Bangalore India

Approximate Nearest-Neighbour Field has been an area of interest in recent research for a wide variety of topics in graphics and multimedia community. Medical image processing is a relatively unaffected field by these developments in ANNF computations, brought about by various extremely efficient algorithms like PatchMatch. In this paper, we use Generalized PatchMatch for Optic Disk detection, in retinal images, and show that by making use of efficient ANNF computations we are able to generate results with 98% accuracy with an average time of 0.5 sec. This is significantly faster than conventional Optic Disk detection methods, which average at 95-97% accuracy with 3-5 sec average computation time.

关键词： Optical imaging Biomedical optical imaging Accuracy Adaptive optics Retina Databases Integrated optics

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A density based method for automatic hairstyle discovery and recognition

A density based method for automatic hairstyle discovery and...

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

作者： Jyotikrishna Dass Monika Sharma Ehtesham Hassan Hiranmay Ghosh Electronics and Communication Engineering Indian Institute of Technology Guwahati India TCS Innovation Labs Delhi TATA Consultancy Services Limited Gurgaon India

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.

关键词： Hair Face image recognition Nose Face recognition image segmentation Internet

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A robust faint line detection and enhancement algorithm for mural images

A robust faint line detection and enhancement algorithm for ...

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

作者： Mrinmoy Ghorai Bhabatosh Chanda Indian Statistical Institute

Mural images are noisy and consist of faint and broken lines. Here we propose a novel technique for straight and curve line detection and also an enhancement algorithm for deteriorated mural images. First we compute some statistics on gray image using oriented templates. The outcome of the process are taken as a strength of the line at each pixel. As a result some unwanted lines are also detected in the texture region. Based on Gestalt law of continuity we propose an anisotropic refinement to strengthen the true lines and to suppress the unwanted ones. A modified bilateral filter is employed to remove the noises. Experimental result shows that the approach is robust to restore the lines in the mural images.

关键词： image restoration Correlation Convolution image edge detection Noise Noise reduction Robustness

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Fuzzy video summarization using key frame extraction

Fuzzy video summarization using key frame extraction

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

作者： Aditi Kapoor K. K. Biswas M. Hanmandlu Amar Nath and Shashi Khosla School of Information Technology Indian Institute of Technology Delhi Hauz Khas New Delhi

In this paper we propose to summarize videos based on key frames. We improve upon the histogram and pixel difference based approach with fuzzy rule based approach and also give a new approach which reduces the computation of framewise differences. We test our methods using fidelity ratio and compression ratio on videos of sports from YouTube and UCF sports dataset, videos of commercials and sitcoms. The results of our methods are seen to be comparable to other state of the art approaches.

关键词： Videos High definition video Redundancy image segmentation Histograms Irrigation Europe

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Estimation of the orientation and distance of a mirror from Kinect depth data

Estimation of the orientation and distance of a mirror from ...

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

作者： Tanwi Mallick Partha Pratim Das Arun Kumar Majumdar Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Indian Institute of Technology Delhi New Delhi Delhi IN

In many common applications of Microsoft Kinect™ including navigation, surveillance, 3D reconstruction, and the like; it is required to estimate the geometry of mirrors or other reflecting surfaces existing in the field of view. This often is difficult as in most positions a mirror does not support diffuse reflection of speckles and hence cannot be seen in the Kinect depth map. A mirror shows up as unknown depth. However, suitably placed objects reflecting in the mirror can provide important clues for the orientation and distance of the mirror. In this paper we present a method using a ball and its mirror image to set-up point-to-point correspondence between object and image points to solve for the geometry of the mirror. With this simple estimators are designed for the orientation and distance of a plane vertical mirror with respect to the Kinect camera. In addition an estimator is presented for the diameter of the ball. The estimators are validated through a set of experiments.

关键词： Mirrors Geometry Cameras Estimation Spatial resolution Three-dimensional displays Noise

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Speeding up SIFT using GPU

Speeding up SIFT using GPU

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

作者： Aniruddha Acharya K R. Venkatesh Babu Video Anaytics Laboratory Indian Institute of Science Bangalore India

Scale Invariant Feature Transform (SIFT) is one of the widely used interest point features. It has been successfully applied in various computer vision algorithms like object detection, object tracking, robotic mapping and large scale image retrieval. Although SIFT descriptors are highly robust towards scale and rotation variations, the high computational complexity of the SIFT algorithm inhibits its use in applications demanding real time response, and in algorithms dealing with very large scale databases. This paper presents a parallel implementation of SIFT on a GPU, where we obtain a speed of around 55 fps for a 640×480 image. One of the main contributions of our work is the novel combined kernel optimization that has led to a significant improvement of 21.79% in the execution speed. We compare our results with the existing implementations in the literature that accelerate SIFT, and find that our implementation has better speedup than the most of them.

关键词： graphics processing units Kernel Feature extraction Convolution Instruction sets Optimization Random access memory

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