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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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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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Brain tumor segmentation from multimodal MR images using rough sets 10

Brain tumor segmentation from multimodal MR images using rou...

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10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Saha, Rupsa Phophalia, Ashish Mitra, Suman K. Dhirubhai Ambani Institute of Information and Communication Technology GandhinagarGujarat382007 India Indian Institute of Information Technology Vadodara GandhinagarGujarat382028 India

Automatic segmentation of brain tumors from Magnetic Resonance images is a challenging task due to the wide variation in intensity, size, location of tumors in images. Defining a precise boundary for a tumor is essential for diagnosis and treatment of patients. Rough set theory, an extension of classical set theory, deals with the vagueness of data by determining the boundary region of a set. The aim of this work is to explore the possibility and effectiveness of using a rough set model to represent the tumor regions in MR images accurately, with Quadtree partitioning and simple K-means as precursors to indicate and limit the possible relevant regions. The advantage of using rough sets lie in its ability to represent the impreciseness of set boundaries, which is one of the major challenges faced in tumor segmentation. Experiments are carried out on the BRATS 2013 and 2015 databases and results are comparable to those reported by recent works. © Springer International Publishing AG 2017.

关键词： Magnetic resonance imaging

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A generative adversarial network for tone mapping HDR images 6th

A generative adversarial network for tone mapping HDR images

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6th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2017

作者： Patel, Vaibhav Amit Shah, Purvik Raman, Shanmuganathan Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar GandhinagarGujarat382007 India Indian Institute of Technology Gandhinagar GandhinagarGujarat382007 India

ISBN: (纸本)9789811300196

A tone mapping operator converts High Dynamic Range (HDR) images to Low Dynamic Range (LDR) images, which can be seen on LDR displays. There has been a lot of research done in the direction of an optimal Tone Mapping Operator which maximizes Tone Mapping Quality Index (TMQI). However, since all the methods approximate Human vision System in one or different way, none of them works for every type of images. We are proposing a novel generative adversarial network to learn a combination of these tone mapping operators. In order to get pixel level accuracy, we are using residual connections between same sized network layers. We compare this method with some of the existing tone mapping operators and observe that our method generates images with comparably high TMQI and indeed works on many different types of images. Because of the residual connections, the network can be scaled to very high dimensional images. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Generative adversarial networks

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An Evolutionary Based Slow and Fast Moving Video Object Detection Scheme Using Compound Markov Random Field Model

An Evolutionary Based Slow and Fast Moving Video Object Dete...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Badri Narayan Subudhi Pradipta Kumar Nanda Department of Electrical Engineering National Institute of Technology Rourkela India Department of Electonics and Telecommunication C. V. Raman College of Engineering Bhubaneswar India

We propose an evolving scheme to detect slow as well as fast moving objects in a video sequence. The proposed scheme employ both spatio-temporal and temporal segmentation to obtain the video object plane and hence detection. We propose a compound Markov random field model as the a priori image model that takes into account the spatial distribution of the current frame, temporal frames and the edge maps of the temporal frames. The spatio-temporal segmentation is cast as a pixel labeling problem and the labels are the MAP estimates. The MAP estimates of a frame are obtained by a hybrid algorithm. The spatial segmentation of a given frame evolves to generate the spatial segmentation of the subsequent frames. The evolved spatial segmentation together with the temporal segmentation produces the Video Object Plane (VOP) and hence detection. Our scheme does require the computation of spatio-temporal segmentation of the initial frame thus speeding up the whole process. The results of the proposed scheme are compared with JSEG method are found to be better in terms of the misclassification error.

关键词： Object detection Markov random fields image segmentation Video sequences Context modeling computer vision Stochastic processes Genetic algorithms Dissolved gas analysis computer graphics

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Object extraction from image using higher order entropy

Object extraction from image using higher order entropy

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International conference on Pattern Recognition

作者： S.K. Pal N.R. Pal Electronics & Communication Sciences Unit Indian Statistical Institute Calcutta India Computer Sciences Unit Indian Statistical Institute Calcutta India

Entropy of order q (depending on the information contained in a sequence of gray levels of length q) and conditional entropy of an image are defined. Using these definitions, two algorithms are formulated and implemented with the help of its co-occurrence matrix. Their superiority for image thresholding (object-background classification) is established.< >

关键词： Entropy Signal processing algorithms image segmentation Histograms Classification algorithms Propellers computer vision graphics

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Change Detection and Object Segmentation: A Histogram of Features-Based Energy Minimization Approach

Change Detection and Object Segmentation: A Histogram of Fea...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Nilanjan Ray Baidya Nath Saha Hong Zhang Department of Computing Science University of Alberta Canada

We consider here a change detection problem: to find regions of change on a test image with respect to a reference image. Unlike the state-of-the-art change detection and background subtraction algorithms that compute only local (pixel location-based) changes, we propose to minimize a novel region-based energy functional based on Bhattacharya coefficient involving histograms of image features. The optimization of the proposed energy functional simply consists of two very efficient searches if a crude segmentation such as a bounding box around the region of change is sufficient. Also, it allows variational optimization via level set-based curve evolution for supervised binary image labeling. The framework is demonstrated to cope well with considerable camera motion and shifts of objects between the test and the reference images. We illustrate encouraging results on finding bounding box around abnormality from brain MRI, object detection for maritime surveillance, and segmenting oil-sand particles from conveyor belt images.

关键词： Object detection Object segmentation Histograms Testing image segmentation Change detection algorithms Pixel Labeling Cameras Magnetic resonance imaging

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Using differential constraints to generate a 3D face model from stereo

Using differential constraints to generate a 3D face model f...

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International conference on Pattern Recognition

作者： R. Lengagne P. Fua O. Monga INRIA-Rocquencourt Le Chesnay France Computer Graphics Laboratory LIG EPFL Lausanne Lausanne Switzerland

We propose a way to incorporate a priori information in a 3D stereo reconstruction process from a pair of calibrated face images. A 3D mesh modeling the surface is iteratively deformed in order to minimize an energy function. Differential information about the object shape is used to generate an adaptive mesh that can fulfil the compacity and the accuracy requirements. Moreover in areas where the stereo information is not reliable enough to accurately recover the surface shape, because of inappropriate texture or bad lighting conditions, we incorporate geometric constraints related to the differential properties of the surface, that can be intuitive or refer to predefined geometric properties of the object to be reconstructed. They can be applied to scalar fields, such as curvature values, or structural features, such as crest lines. Therefore, we generate a 3D face model using computer vision techniques that is compact, accurate and consistent with the a priori knowledge about the underlying surface.

关键词： Surface reconstruction Stereo image processing Stereo vision image reconstruction Shape Surface texture Deformable models Mesh generation Face detection computer vision

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Character Segmentation of Handwritten Bangla Text by Vertex Characterization of Isothetic Covers

Character Segmentation of Handwritten Bangla Text by Vertex ...

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

作者： Soumen Bag Partha Bhowmick Gaurav Harit Arindam Biswas Computer Sc. & Engineering Department Indian Institute of Technology Kharagpur India Computer Sc. & Engineering Department Indian Institute of Technology Rajasthan India Computer Sc. & Engineering Department BESU Shibpur India

Segmentation of cursive handwriting is one of the most challenging problems in the area of handwritten character recognition. In this paper, we propose a novel approach towards character segmentation in a handwritten document. It is based on the vertex characterization of outer isothetic polygonal covers so that each cover corresponds to a particular word or part of a word. The proposed method has the potential to segment skewed text without deskewing them. Experiment is done on several Bangla handwritings of different individuals. The average success rate is 96.04\%. This method can be considered as a significant preprocessing step towards the development of a handwritten Bangla OCR system.

关键词： image segmentation Optical character recognition software Character recognition computers Accuracy Feature extraction Reservoirs

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Wavelet image Resizing in the Block DCT Space

Wavelet Image Resizing in the Block DCT Space

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

作者： Kapinaiah Viswanath Jayanta Mukherjee Prabir Kumar Biswas Department of Telecommunication Engineering SIT-Tumkur India Department of CS&E Indian Institute of Technology Kharagpur India Department of E&ECE Indian Institute of Technology Kharagpur India

In this paper, we present algorithms for resizing and transcoding of images in the transform domain. The approach is based on wavelet filtering (analysis/synthesis) along with downsampling/upsampling operation in the block DCT space. We use linear filtering in the block DCT domain to perform convolution. To obtain results equivalent to linear convolution, filtering is performed on the three adjacent blocks. To reduce the complexity, we perform sampling rate change and filtering operations in a single combined step. The proposed approach achieves the best performance in terms of quality compared to the DCT domain technique.

关键词： Discrete cosine transforms Transcoding Wavelet domain Wavelet analysis Discrete wavelet transforms

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S-VQA: Sentence-Based Visual Question Answering 23

S-VQA: Sentence-Based Visual Question Answering

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proceedings of the fourteenth indian conference on computer vision, graphics and image processing

作者： Sanchit Pathak Garima Singh Ashish Anand Prithwijit Guha Data Science (Interdisciplinary) Indian Institute of Technology Guwahati IN Department of Computer Science and Engineering Indian Institute of Technology Guwahati IN Department of Electronics and Electrical Engineering IIT Guwahati IN

ISBN: (纸本)9798400716256

Visual Question Answering (VQA) system responds to a natural language question in context of an image. This problem has been primarily formulated as a classification problem with the answers as the finite number of classes. Thus, the generated response consists of a single word or a short phrase. However, this also limits the linguistic capabilities of such a system. In contrast, this work presents a Sentence-based VQA (S-VQA) which responds to questions with complete sentences as answers. The first contribution of this work is the development of a dataset from the Task Directed image Understanding Challenge (TDIUC) VQA dataset using natural language rules and pretrained para-phrasers. This new dataset is referred to as TDIUC-SVQA. The second contribution involves the performance evaluation of multiple models on the TDIUC-SVQA dataset. This is performed by using two multi-modal models. The Bottom-Up Top-Down Attention based VQA model is combined with LSTM decoder and Attention-on-Attention Network for answer generation. The proposed models are observed to provide improved results compared to the baseline model.

关键词： AoANet

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