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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951-960 订阅

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Tsallis and Renyi's Embedded Entropy based Mutual Information for Multimodal image Registration

Tsallis and Renyi's Embedded Entropy based Mutual Informatio...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sahoo, Subhaluxmi Nanda, P. K. Samant, Sunita Siksha O Anusandan Univ Inst Tech Educ & Res Dept Elect & Instrumentat Engn Bhubaneswar 751030 Orissa India

ISBN: (纸本)9781479915880

In this paper, an embedded entropy based image registration scheme has been proposed. Here, Tsallis and Renyi's entropy have been embedded to form a new entropic measure. This parametrized entropy has been used to determine the weighted mutual information (MI) for the CT and MR brain images. The embedded mutual information has been maximized to obtain registration. This notion of embedded mutual information has also been validated in feature space registration. The mutual information with respect to the registration parameter has been found to be a nonlinear curve. It has been found that the feature space registration resulted in higher value mutual information and hence registration process could be smoother. We have used Simulated Annealing algorithm to determine the maximum of this embedded mutual information and hence register the images.

关键词： Embedded Entropy Mutual Information and image Registration

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Word Recognition in Natural Scene and Video images using Hidden Markov Model

Word Recognition in Natural Scene and Video Images using Hid...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Roy, Sangheeta Roy, Partha Pratim Shivakumara, Palaiahnakote Pal, Umapada Tata Consultancy Serv Kolkata India Indian Stat Inst CVPR Unit Kolkata India Univ Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781479915880

Text recognition from a natural scene and video is challenging compared to that in scanned document images. This is due to the problems of text on different sources of various styles, font variation, font size variations, background variations, etc. There are approaches for word segmentation from video and scene images to feed the word image into OCRs. Nevertheless, such methods often fail to yield satisfactory results in recognition. Therefore, in this paper, we propose to combine Hidden Markov Model (HMM) and Convolutional Neural Network (CNN) to achieve good recognition rate. Sequential gradient features with HMM help to find character alignment of a word. Later the character alignments are verified by Convolutional Neural network (CNN). The approach is tested on both video and scene data to show the effectiveness of the proposed approach. The results are found encouraging.

关键词： Hidden Markov models Videotapes word recognition natural scenes Printed text recognition images document image Word FONT

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Fast Moving- Object Detection in H.264/AVC Compressed Domain for Video Surveillance

Fast Moving- Object Detection in H.264/AVC Compressed Domain...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Tom, Manu Babu, R. Venkatesh Indian Inst Sci SERC Video Analyt Lab Bangalore 560012 Karnataka India

ISBN: (纸本)9781479915880

This paper discusses a novel fast approach for moving object detection in H.264/AVC compressed domain for video surveillance applications. The proposed algorithm initially segments out edges from regions with motion at macroblock level by utilizing the gradient of quantization parameter over 2D-image space. A spatial median filtering of the segmented edges followed by weighted temporal accumulation accounts for whole object segmentation. To attain sub-macroblock (4 x 4) level precision, the size of macroblocks (in bits) is interpolated using a two tap filter. Partial decoding rules out the complexity involved in full decoding and gives fast foreground segmentation results. Compared to other compressed domain techniques, the proposed approach allows the video streams to be encoded with different quantization parameters across macroblocks thereby increasing flexibility in bit rate adjustment.

关键词： Motion Segmentation Compressed Domain H.264/AVC Video Surveillance QP-delta

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Multiscale Noise-Adaptive Homomorphic Filtering based Speckle Denoising in Laser Speckle Imaging

Multiscale Noise-Adaptive Homomorphic Filtering based Speckl...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Basak, Kausik Mahadevappa, Manjunatha Dutta, Pranab Kumar Indian Inst Technol Sch Med Sci & Technol Kharagpur 721302 W Bengal India Indian Inst Technol Dept Elect Engn Kharagpur 721302 W Bengal India

ISBN: (纸本)9781479915880

Speckle pattern forms as a result of constructive and destructive interference due to the phase difference involved in multiple backscattered photons. In coherent optical probing, speckle has a dual role as an insidious form of noise as well as a source of information for sample microstructure. This paper focuses on designing of a multiscale noise adaptive homomorphic filter (MNAHF) for speckle noise reduction (keeping the signal-carrying speckle) in laser speckle imaging (LSI). The operation has been performed based on the calculation of local statistics within a sliding window region over a successive number of time frames. It has been shown that MNAHF outperforms other speckle denoising filters from the point of image quality assessment and better visualization. It exhibits lower mean square error and Minkowski metric values with better image quality, intact structural similarity and superior signal to noise ratio relative to others. Therefore, over a wider spectrum, this work brings out the scope of speckle noise reduction prior to further large scale processing for automated segmentation, texture analysis and image based classification techniques in clinical study of laser speckle images.

关键词： Laser speckle optical imaging spatial filtering speckle denoising homomorphic filter

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An Optimized Derivative Projection Warping Approach For Moving Platform Video Stabilization

An Optimized Derivative Projection Warping Approach For Movi...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Shukla, Deepika Jha, Rajib Kumar Indian Inst Informat Technol Design & Mfg Jabalpu Elect & Commun Engn Jabalpur 482005 India Indian Inst Technol Dept Elect Engn Patna 800013 Bihar India

ISBN: (纸本)9781479915880

This paper presents an optimized and efficient video stabilization technique based on projection curve warping. In most of the recorded videos, the relative displacement between two consecutive frames goes from 3-4 pixel for hand-held and 25-30 for moving platform applications. Based on this experimental data, the use of Sakoe-Chiba band with fixed window size has been proposed for constraining distance matrix estimation, in the dynamic time warping algorithm. In the existing projection based stabilization techniques, intensity values are matched for motion estimation. Any change in the local intensity values either induced due to intensity variation, moving objects or scene variation, causes error in the estimated motion. To overcome this problem, a higher level feature i.e. shape of the projection curve has been incorporated by matching the local derivative of curve instead of the intensity values itself. Robustness and time efficiency of the proposed technique is measured in terms of interframe transformation fidelity and processing time respectively.

关键词： Sakoe-Chiba band dynamic time warping motion estimation video stabilization ITF

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Enhancement of Camera Captured Text images with Specular Reflection

Enhancement of Camera Captured Text Images with Specular Ref...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Visvanathan, Aishwarya Chattopadhyay, T. Bhattacharya, Ujjwal Kolkata Tata Consultancy Serv Ltd Innovat Lab Kolkata India Indian Stat Inst CVPR Unit Kolkata India

ISBN: (纸本)9781479915880

Specular reflection of light degrades the quality of scene images. Whenever specular reflection affects the text portion of such an image, its readability is reduced significantly. Consequently, it becomes difficult for an OCR software to detect and recognize similar texts. In the present work, we propose a novel but simple technique to enhance the region of the image with specular reflection. The pixels with specular reflection were identified in YUV color plane. In the next step, it enhances the region by interpolating possible pixel values in YUV space. The proposed method has been compared against a few existing general purpose image enhancement techniques which include (i) histogram equalization, (ii) gamma correction and (iii) Laplacian filter based enhancement method. The proposed approach has been tested on some images from ICDAR 2003 Robust Reading Competition image database. We computed a Mean Opinion Score based measure to show that the proposed method outperforms the existing enhancement techniques for enhancement of readability of texts in images affected by specular reflection.

关键词： specular reflection images mean opinion score intelligibility Refractive surgery enhancement texts Cameras YUV imagery (Psychotherapy)

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Mean Shift Clustering based Outlier Removal for Global Motion Estimation

Mean Shift Clustering based Outlier Removal for Global Motio...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Okade, Manish Biswas, Prabir Kumar BVB Coll Engn & Technol Dept Elect & Commun Engn Hubli India Indian Inst Technol Dept Elect & Elect Commun Engn Kharagpur 721302 W Bengal India

ISBN: (纸本)9781479915880

This paper investigates a novel motion vector outlier rejection method based on using mean shift clustering on block motion vectors. The accuracy of compressed domain global motion estimation techniques is largely influenced by its ability to counter the outlier motion vectors. These outliers occur in the block motion vector field due to moving objects, noise or due to large matching errors as a result of the encoders priority on rate distortion optimization. In the present work it is shown that by using mean shift clustering on block motion vectors, those clusters which correspond to outlier motion vectors can be identified. Once detected these clusters are kept out of the global motion estimation process thereby increasing the robustness of estimated camera parameters. The proposed method is compared with existing state-of-the-art outlier removal methods using synthetic and real video sequences to establish and validate its superiority.

关键词： outlier motion vectors mean shift clustering global motion estimation compressed domain

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Spatial Variance of Color and Boundary Statistics for Salient Object Detection

Spatial Variance of Color and Boundary Statistics for Salien...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Roy, Sudeshna Das, Sukhendu Indian Inst Technol Dept Comp Sci & Engn Visualizat & Percept Lab Madras 600036 Tamil Nadu India

ISBN: (纸本)9781479915880

Bottom-up saliency detection algorithms identify distinct regions in an image, with rare occurrence of local feature distributions. Notable among those works published recently, use local and global contrast, spectral analysis of the entire image or graph based feature mapping. Whereas, we propose a novel unsupervised method using color compactness and statistical modeling of the background cues, to segment the salient foreground region and thus the salient object. At the first stage of processing, the image is segmented into clusters using color feature. First component proposed for our saliency measure combines disparity in color and spatial distance between patches. In addition to rarity of feature, we propose another component for saliency computation that estimates the divergence of the color of a patch from those in the set of patches at the boundary of the image, representing the background. Combination of these two complementary components provides a much improved saliency map for salient object detection. We verify the performance of our proposed method of saliency detection on two popular benchmark datasets, with one or more salient regions and diverse saliency characteristics. Experimental results show that our method outperforms many existing state-of-the-art methods.

关键词： Object detection Color images imagery (Psychotherapy) color feature image boundary layer statistical models (nuclear) Patches Boundary

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Duplicate open page removal from video stream of book flipping

Duplicate open page removal from video stream of book flippi...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Chakraborty, Dibyayan Roy, Partha Pratim Alvarez, Jose M. Pal, Umapada Ramakrishna Mission Vivekananda Univ Dept Comp Sci Howrah India Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata 108 India NICTA Sydney NSW Australia

ISBN: (纸本)9781479915880

Book flipping scanning refers to the process of recording a book while the user performs the flipping action of its pages. In recent years it has gained much attention as it reduces the workload of book digitization significantly. It is a challenging task because flipping at random speed and direction causes difficulties to identify distinct open page images (OPI) which represent each page of the book. In this paper, we propose a fast technique for removing duplicate open pages introduced in the video stream due to erroneous flipping. We present an algorithm that exploits cues from edge information of flipping pages. The nature of the cues extracted from the region of interest (ROI) of the frame, determines the flipping or an open state of a page whereas temporal position a flipping page determines the direction of the flipping. Combining these information we decide whether an open page image is a duplicate or not. Experiments are performed on video documents recorded using a standard resolution camera to validate the duplicate open page removal algorithm and we have obtained 95% accuracy.

关键词： Book flipping scanning Video document image OPI

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High Quality Depth Map Estimation by Kinect Upsampling and Hole Filling using RGB Features and Mutual Information

High Quality Depth Map Estimation by Kinect Upsampling and H...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Chahal, Nidhi Chaudhury, Santanu Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781479915880

High quality depth map estimation is required for better visualization of 3D views as there is great impact of depth map quality on overall 3D image quality. If the depth is estimated from conventional ways using two or more images, some defects come into picture, mostly in regions without texture. We utilised Microsoft Kinect RGBD dataset to obtain input color images and depth maps which also includes some noise factors. We proposed a method to remove this noise and get quality depth images. First the color and depth images are aligned to each other using intensity based image registration. This method of image alignment is mostly used in medical field, but we applied this technique to correct kinect depth maps by which one can avoid cumbersome task of feature based point correspondence between images. There is no requirement of preprocessing or segmentation steps if we use intensity based image alignment method. Second, we proposed an algorithm to fill the unwanted gaps in kinect depth maps and upsampled it using corresponding high resolution color image. Finally we applied 9x9 median filtering on implementation results and get high quality and improved depth maps.

关键词： image registration mutual information geometric transformations

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