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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1031-1040 订阅

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

作者： Nidhi Chahal Santanu Chaudhury Department of Electrical Engineering Indian Institute of Technology Delhi India

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 9×9 median filtering on implementation results and get high quality and improved depth maps.

关键词： Mutual information image color analysis Filtering Color Joints image resolution image registration

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Classification of hardwood species using ANN classifier

Classification of hardwood species using ANN classifier

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

作者： Arvind R. Yadav M. L. Dewal R. S. Anand Sangeeta Gupta Department of Electrical Engineering Indian Institute of Technology Roorkee Roorkee India Botany Division Forest Research Institute Dehradun Dehradun India

In this paper, an approach for the classification of different hardwood species of open access database, using texture feature extraction and supervised machine learning technique has been implemented. Edges of complex cellular structure of microscopic images of hardwood are enhanced with the application of Gabor filter, and Gray Level Co-occurrence Matrix (GLCM) as an effective texture feature extraction technique is being revalidated. About, 44 features have been extracted from GLCM; these features have been further normalized in the range [0.1, 1]. Multilayer Perceptron Backpropagation Artificial Neural Network have been used for classification. Experiments conducted on 25 wood species have resulted in recognition accuracy of about 88.60% and 92.60% using Levenberg-Marquardt backpropagation training function with two different datasets for training, validation and testing ratio (70%, 15%, 15% and 80%, 10%, 10%) respectively. Proposed methodology can be extended with optimized machine learning techniques for online identification of wood.

关键词： Feature extraction Training Accuracy Microscopy Gabor filters Backpropagation Artificial neural networks

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Shape recognition based on shape-signature identification and condensibility: Application to underwater imagery

Shape recognition based on shape-signature identification an...

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

作者： Jeet Banerjee Ranjit Ray Siva Ram Krishna Vadali Ritwik Kumar Layek Sankar Nath Shome Electronics and Electrical Communication Dept Indian Institute of Technology Kharagpur Kharagpur West Bengal Robotics and Automation Div CSIR-Central Mechanical Engineering Research Institute Durgapur West Bengal Central Mechanical Engineering Research Institute CSIR Durgapur West Bengal IN

In this paper, a shape recognition method is proposed for a few common geometrical shapes including straight line, circle, ellipse, triangle, quadrilateral, pentagon and hexagon. In the present work, two indices namely Unique Shape Signature (USS) and Condensibility (C) are employed for shape recognition of an object. Using the USS index, all the above mentioned non-circular shapes are neatly recognized, whereas, the C index recognized the circular objects. An added advantage of the proposed method is that it can further differentiate triangles, quadrilaterals and both symmetric and non-symmetric shapes of pentagon and hexagon using distance variance (V ar(d si )) parameter calculated from USS. Applying the proposed method on above mentioned shapes, an overall recognition rate of 98.80% is achieved on several simulated and real objects of different shapes. Proposed method has also been compared with two existing methods, presents better result. Performance of the proposed method is illustrated by applying it on underwater images and it is observed to perform satisfactory on all the images under test.

关键词： Shape image edge detection Object recognition image color analysis Indexes Standards

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Surface fitting in SPECT imaging useful for detecting Parkinson's Disease and Scans Without Evidence of Dopaminergic Deficit

Surface fitting in SPECT imaging useful for detecting Parkin...

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

作者： R. Prashanth Sumantra Dutta Roy Pravat K. Mandal Shantanu Ghosh Department of Electrical Engineering Indian Institute of technology Delhi New Delhi India Indian Institute of Technology Delhi New Delhi Delhi IN Neurospectroscopy and Neuroimaging Laboratory National Brain Research Centre India Martinos Center for Biomedical Imaging Massachusetts General Hospital and Harvard Medical School Boston Massachusetts USA

Dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with 123 I-Ioflupane have shown to increase the diagnostic accuracy in Parkinson's Disease (PD). Studies show that around 10% of subjects who are clinically diagnosed as PD, have SPECT scans in the normal range and are called Scans Without Evidence of Dopaminergic Deficit (SWEDD) subjects. Subsequent follow-up on these subjects has indicated that they are unlikely to have PD. Detection and differentiation of PD and SWEDD is problematic in the early stages of the disease. Early and accurate diagnosis of PD and also SWEDD is crucial for early management, avoidance of unnecessary medical examinations and therapies; and their side-effects. We in our paper, use the SPECT images from 35 Normal, 36 PD and 38 SWEDD subjects as obtained from the Parkinson's Progression Markers Initiative (PPMI) database, to carry out intensity-based surface fitting using polynomial model. This is the first time that such kind of modeling is carried out on the SPECT images for the characterization of PD. Our results show that the surface profile in terms of model coefficients and goodness-of-fit parameters is different for Normal, Early PD and SWEDD subjects. Such kind of modeling may aid in the diagnosis of early PD and SWEDD from SPECT images.

关键词： Single photon emission computed tomography Surface fitting Polynomials Fitting image segmentation Biomedical imaging

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Accurate and efficient rendering of detail using directional distance maps 12

Accurate and efficient rendering of detail using directional...

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Mehra, Ravish Kumar, Subodh Department of Computer Science Indian Institute of Technology Delhi India

ISBN: (纸本)9781450316606

We present an efficient GPU technique for rendering rich geometric detail (e.g., surface mesostructure) of complex surfaces. We use sphere-tracing aided by directional distance maps (DDMs) to quickly find ray-mesostructure intersection. High accuracy is achieved by analytically detecting such intersections, and space requirement is significantly reduced by distance map compression. Our technique can handle complex scenes containing both height-field and non height-field mesostructures in real time, with correct self-occlusion, self-shadow, interpenetrations and silhouettes. We demonstrate our algorithm on a variety of test scenarios and compare it with previous techniques. © 2012 ACM.

关键词： graphics processing unit

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PCA based video denoising in a non-local means framework 12

PCA based video denoising in a non-local means framework

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Bhujle, Hemalata Chaudhuri, Subhasis Vision and Image Processing Lab. Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai India

ISBN: (纸本)9781450316606

Nonlocal means (NLM) video denoising algorithm though provide very competitive results, suffer from high computational cost. We propose to reduce the computations through the concept of dimensionality reduction using principle component analysis (PCA). image neighbourhood representations are projected onto a lower dimensional subspace determined by PCA and weights are computed in this reduced subspace. Principle components are computed globally for an entire video shot having similar frames, which reduces computations drastically. We have used a technique of histogram difference to group the frames with similar visual content. We have achieved an improvement in accuracy in addition to reducing the computation. The proposed method is shown to outperform all other nonlocal means related video denoising methods. © 2012 ACM.

关键词： Principal component analysis

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Realtime motion detection based on the spatio-temporal median filter using GPU integral histograms 12

Realtime motion detection based on the spatio-temporal media...

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Poostchi, Mahdieh Palaniappan, Kannappan Bunyak, Filiz Seetharaman, Guna Dept. of Computer Science University of Missouri Columbia MO United States Air Force Research Laboratory Rome NY United States

ISBN: (纸本)9781450316606

Motion detection using background modeling is a widely used technique in object tracking. To meet the demands of real-time multi-target tracking applications in large and/or high resolution imagery fast parallel algorithms for motion detection are desirable. One common method for background modeling is to use an adaptive 3D median filter that is updated appropriately based on the video sequence. We describe a parallel 3D spatiotemporal median filter algorithm implemented in CUDA for many core graphics processing Unit (GPU) architectures using the integral histogram as a building block to support adaptive window sizes. Both 2D and 3D median filters are also widely used in many other computer vision tasks like denoising, segmentation, and recognition. Although fast sequential median algorithms exist, improving performance using parallelization is attractive to reduce the time needed for motion detection in order to support more complex processing in multi-target tracking systems, large high resolution aerial video imagery and 3D volumetric processing. Results show the frame rate of the GPU implementation was 60 times faster than the CPU version for a 1K x 1K image reaching 49 fr/sec and 21 times faster for 512 x 512 frame sizes reaching 194 fr/sec. We characterize performance of the parallel 3D median filter for different image sizes and varying number of histogram bins and show selected results for motion detection. © 2012 ACM.

关键词： graphics processing unit

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Digital restoration of damaged mural images 12

Digital restoration of damaged mural images

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Purkait, Pulak Chanda, Bhabatosh Indian Statistical Institute Kolkata India

ISBN: (纸本)9781450316606

Patch-based techniques are proven to generate promising results and outperform many of the existing state-of-art techniques for most of the applications in digital image processing. In this work we develop a patch based coherent texture synthesis technique. A patch-based anisotropic diffusion techniques combined with a novel high-frequency generating technique that can enhance line/brush strokes is also proposed. Though these techniques can be applied to many different image processing applications, here we have limited ourselves in the application to interactive digital mural painting recovery/restoration. Some empirical and practical evidence for its high quality texture synthesis and restoration for mural paintings are also presented. The experimental results show the effectiveness of the proposed algorithm. © 2012 ACM.

关键词： Restoration

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image retargeting using controlled shrinkage 12

Image retargeting using controlled shrinkage

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Pal, Rajarshi Mitra, Pabitra Mukherjee, Jayanta Institute for Development and Research in Banking Technology Hyderabad India Indian Institute of Technology Kharagpur India

ISBN: (纸本)9781450316606

The problem of retargeting a larger image in a small display is to maintain recognizability of the objects. The retargeting scheme proposed in this paper provides a suitable solution to this. The input image is partitioned into rectangular strips such that alternate strips contain important or unimportant objects. Each of these rectangular strips shrinks in size to fit the entire image into the small display. Strips containing unimportant objects shrink at a higher rate than those containing important objects. It is experimentally found that this scheme performs better than many existing schemes. An estimate for the range of values for shrinkage controlling parameters is also attempted here. © 2012 ACM.

关键词： Shrinkage

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Estimation of the area of mouth opening during speech production 12

Estimation of the area of mouth opening during speech produc...

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Saha, Sudipan Pandey, Prem C. Department of Electrical Engineering Indian Institute of Technology Bombay Mumbai-400076 Maharashtra India

ISBN: (纸本)9781450316606

Estimation of the area of mouth opening from a video of the speaker's face and processing of the simultaneously recorded speech signal can be used for estimation of vocal tract shape during speech production. A technique is presented to estimate the area of mouth opening, using a processing based on contrast enhancement with multi-threshold binarization and connected component detection for reducing the errors in estimating the vertical opening due to the presence of teeth and tongue in mouth opening. The method is tested on vowel utterances from 12 speakers. © 2012 ACM.

关键词： Speech

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