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检索条件"任意字段=Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing"

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Single image dehazing with varying atmospheric light intensity

Single image dehazing with varying atmospheric light intensi...

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

作者： Sanchayan Santra Bhabatosh Chanda Indian Statistical Institute Kolkata India

images taken in bad weather conditions like haze and fog suffer from loss of contrast and color shift. The object radiance is attenuated in the atmosphere and the atmospheric light is added to the scene radiance creating a veil like semi-transparent layer called airlight. The methods proposed till now assumes that the atmospheric light is constant throughout the image domain, which may not be true always. Here we propose a method that works under the relaxed assumption that the color of atmospheric light is constant but its intensity may vary in the image. We use the color line model to estimate the contribution of airlight in each patch and interpolate at places where the estimate is not reliable. We apply reverse operation to recover the haze free image.

关键词： image color analysis Mathematical model Colored noise Atmospheric modeling Meteorology Observers Covariance matrices

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SIFT based view invariant watermarking for DIBR 3D image

SIFT based view invariant watermarking for DIBR 3D image

引用

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

作者： Shuvendu Rana Vishavdeep Mattu Arijit Sur Department of CSE Indian Institute of Technology Guwahati India

In this paper, a view invariant watermarking scheme is proposed for depth image based rendering (DIBR) 3D image representation. To make the scheme invariant against view synthesis process, the watermark is inserted in the image locations selected by the SIFT (Scale-invariant feature transform) feature points. A novel SIFT feature based coefficient selection scheme has been implemented for watermark embedding by exploiting the shift invariance and directional property of the DIBR based view synthesis process. A coefficient partitioning based blind watermarking method has been included to make the scheme more efficient. A comprehensive set of experiments have been carried out to justify the robustness of the proposed scheme against the view synthesis attack.

关键词： Watermarking Feature extraction Three-dimensional displays Discrete cosine transforms image representation Robustness Visualization

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Entropy thresholding based microaneurysm detection in fundus images

Entropy thresholding based microaneurysm detection in fundus...

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

作者： Vineeta Das N. B. Puhan Rashmi Panda School of Electrical Sciences Indian Institute of Technology Bhubaneswar India

Microaneurysms are small red dots that occur on the retina during preliminary stage of Diabetic Retinopathy. computer aided microaneurysm screening is necessary to prevent the aggravation of the disease and further vision loss. In this paper, Shannon and Tsallis entropy thresholding in conjunction with Naïve Bayes classifier is suggested for microaneurysm detection. Various shape and intensity based features are extracted to eliminate the falsely detected candidates. The proposed method is evaluated by plotting the FROC curves using the Retinopathy Online Challenge (ROC) and DIARETDB1 databases. The proposed method achieves high sensitivity values of 0.421 and 0.477 (at false positive rate of 8) using Shannon and Tsallis entropy thresholding which is better than some existing methods.

关键词： Entropy Databases Biomedical imaging Retinopathy Blood vessels Matched filters Training

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A robust watermarking scheme against re-compression attack for H.265/HEVC

A robust watermarking scheme against re-compression attack f...

引用

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

作者： Sibaji Gaj Arijit Sur Prabin Kumar Bora Department of CSE Indian Institute of Technology Guwahati Assam India Department of EEE Indian Institute of Technology Guwahati Assam India

In this paper, a compressed domain blind watermarking scheme is proposed which embeds the watermark by altering the number of nonzero transform co-efficients (NNZ) of 4 × 4 transform blocks of the HEVC video sequence. To embed the watermark, firstly, temporally homogeneous blocks having relatively less motion are selected. In this work, watermark is inserted in the Intra (I) frame and the motion characteristics of the I frame has been determined using the motion information of the Inter (P or B) predicted frames of its close neighborhood. The watermark is embedded by altering the NNZ difference of 4 × 4 transform blocks in the consecutive intra predicted frames. A comprehensive set of experiments is carried out to show that the scheme is robust against re-compression attacks while maintaining a descent visual quality (PSNR), the bit increase rate (BIR) of the watermarked video.

关键词： Watermarking Robustness Transforms Video sequences Encoding Visualization Standards

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Sparse representation based classifier to assess video quality

Sparse representation based classifier to assess video quali...

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

作者： Manoj Sharma Santanu Chaudhury Brejesh Lall Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India

ISBN: (纸本)9781467385657

This paper describes a sparse representation based approach to learn a classifier for assessing the video quality without a reference. First we calculate the natural scene statistics (NSS) based spatial features of each frame/image and then learn a dictionary by K-SVD algorithm from NSS features of correct frames. In this work we identified the fact that correct frame can be represented precisely in terms of dictionary atoms but while representing a distorted frame, the error drastically increases with increase in distortion thus we can easily classify the frames as correct and distorted based on error score calculated by sparse representation framework. This framework has been validated on two datasets and we observe improved accuracies as compared to state-of-art algorithms.

关键词： Dictionaries Distortion image quality Video recording Quality assessment Classification algorithms Distortion measurement

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Segmenting printed text and handwritten annotation by Spectral Partitioning

Segmenting printed text and handwritten annotation by Spectr...

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

作者： Shilpa Pandey Gaurav Harit Computer Science & Engineering Indian Institute of Technology Jodhpur India

This paper addresses the problem of segmenting handwritten annotations on scientific research papers. The motivation of this work is to geometrically segment the complex cases of handwritten annotations, including marks, cuts and special symbols along, with the regular text. Our work particularly focuses on documents that have multi-oriented handwritten [1] annotations rather than annotations in controlled scenario [2]. Spectral Partitioning is adopted as the segmentation scheme to separate the printed text and annotations. A new feature Envelope Straightness is developed and included in our feature set. This leads to an improvement of accuracy over the state-of-the-art features. The experiments are performed on two datasets: 40 documents authored by two writers from IAM dataset, comprising only printed and handwritten text and a self created dataset of 40 scientific papers from various proceedings annotated by a reader, comprising varied types of annotations. In the framework of spectral partitioning, our feature set has achieved a recall of 98.39% for printed text and precision of 85.40% for handwritten annotations on our dataset. For IAM dataset our feature set has achieved a recall of 81.89% for printed text and a precision of 69.67% for handwritten annotations. The results achieved on both dataset are better compared with results obtained using [3] [1].

关键词： Feature extraction Shape Layout image segmentation Noise measurement Clustering algorithms

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RST invariant multi view 3D image watermarking using DWT and SVD

RST invariant multi view 3D image watermarking using DWT and...

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

作者： Sibaji Gaj Shuvendu Rana Anirban Lekharu Arijit Sur Prabin Kumar Bora Multimedia Lab Indian Institute of Technology Guwahati India Department of EEE Indian Institute of Technology Guwahati India

In this paper, a multi-view stereo image watermarking scheme is proposed to resist the RST (rotation, scaling and translation) attack. To make the scheme resilient to RST, the coefficients of Singular Value Decomposition (SVD) from both left and right views have been used for insertion of the watermark bits. 2D-DWT (Discrete wavelet transform) is used as a preprocessing step to get more correlated SVD coefficients of the left and right view such that the visual degradation due to embedding can be reduced. In this work, a blind embedding scheme is proposed by altering the selected SVD coefficients to improve the robustness of the embedding scheme. A comprehensive set of experiments have been performed to justify the robustness of the proposed scheme against RST attack. Moreover, this scheme can be used to detect the view swapping attack using DIBR technique.

关键词： Watermarking Three-dimensional displays Discrete wavelet transforms Robustness Matrix decomposition Resists

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Recommendation of complementary garments using ontology

Recommendation of complementary garments using ontology

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

作者： Deepti Goel Santanu Chaudhury Hiranmay Ghosh Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi TCS Innovation Labs TATA Consultancy Services Limited Gurgaon

This paper proposes a novel recommendation engine to suggest coordinated outfits to the users that complements each other. The proposed recommendation model encodes subjective knowledge of clothing experts in Multimedia Web Ontology Language (MOWL) and makes use of evidential and causal reasoning scheme to deal with the media properties of concepts. Our approach automatically identifies the user visual personality and interprets the contextual meaning of media features of the garments in the context of input query image. As a result, personalized complementary garments based on occasion of wear are recommended to the user. We have validated our approach with garment preferences of various models with a large collection of shirts and trousers, collected from various websites.

关键词： Clothing image color analysis Media Ontologies Cognition Context Visualization

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Information set based approach for salient object detection

Information set based approach for salient object detection

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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 New Delhi Department of Computer Science and Engineering Indian Institute of Technology Delhi New Delhi

Human attention tends to get focused on the most prominent components of a scene which are in sharp contrast with the background. These are termed as salient regions. Saliency is defined in terms of local and global feature contrasts. The human brain perceives an object of salient type based on its difference with the surroundings in terms of color and texture. There have been many color based approaches in the past for salient object detection. In this paper, we define the uncertainty of a window being salient or background in terms of information extracted from different color components. The uncertainty associated with the elements of a fuzzy set is described by a membership function, which gives the degree of association of each element to the set. The overall uncertainty is sought to be quantified by an entropy function. To locate the salient parts of the image, we make use of the entropy to compute a new set of features from color and luminance components of the image. Extensive comparisons with the state-of-the-art methods in terms of precision, recall and F-Measure are made on a publicly available dataset to prove the effectiveness of this approach.

关键词： Entropy image color analysis Uncertainty Feature extraction Object detection Visualization Probabilistic logic

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Robust control of applications by hand-gestures

Robust control of applications by hand-gestures

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

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

We use the RGB-D technology of Kinect to control an application with hand-gestures. We use PowerPoint for test. The system can start/end PPT, navigate between slides, capture or release the control of the cursor, and control it through natural gestures. Such a system is useful and hygienic in the kitchen, lavatories, hospital ICUs for touch-less surgery, and the like. The challenge is to extract meaningful gestures from continuous hand motions. We propose a system that recognizes isolated gestures from continuous hand motions for multiple gestures in real-time. Experimental results show that the system has 96.48% precision (at 96.00% recall) and performs better than the Microsoft Gesture Recognition library for swipe gestures.

关键词： Hidden Markov models Trajectory Hip Gesture recognition Tracking Navigation Training

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