Charts are powerful tools for visualizing and comparing data. Representation of information through charts grows with time due to its easy and aesthetically attractive structure. With the increase in the number of doc...
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A novel nonlinear cooperative approach to image denoising and restoration is presented. Samples from the image field with similar characteristics are first grouped into clusters by first performing image decomposition...
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A novel nonlinear cooperative approach to image denoising and restoration is presented. Samples from the image field with similar characteristics are first grouped into clusters by first performing image decomposition based on the Mumford-Shah model using a total variational framework and performing fuzzy c-means clustering within each image partition. Samples within each cluster are then aggregated using an cooperative Bayesian estimation method based on information from all the samples to provide a nonlinear estimate of the original image. The proposed method exploits information redundancy within each cluster to denoise and restore the original image. Furthermore, the proposed cooperative Bayesian estimation method is capable of suppressing noise and reducing image degradation while preserving image detail by utilizing intra-cluster statistics. The experimental results using different types of images demonstrate that the proposed algorithm provides state-of-the-art image denoising performance in terms of both peak signal-to-noise ratio (PSNR) and subjective visual quality.
In recent days, it is found that Synthetic Aperture Radar (SAR) images can be a very useful mode for observing and understanding the surface of Earth. The images formed under SAR modality usually suffer from multiplic...
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The introduction of metrology in engineering opened out new avenues and today this is an established and expanding field of engineering. From a modest beginning of simple inspection of parts to ensure quality, today i...
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ISBN:
(纸本)007451623X
The introduction of metrology in engineering opened out new avenues and today this is an established and expanding field of engineering. From a modest beginning of simple inspection of parts to ensure quality, today it has grown into a vast field of specialised technology. Indications are that there is more to come in this field with the introduction of high precision and automation in manufacture. Due to the significant role played by metrology in present day manufacture, the term Manufacturing Metrology sounds more appropriate than any of the terms previously used. New areas like robot metrology position measurements of robot within its large work zone, further integration of inspection with manufacture, computervision and imageprocessing techniques etc. are developing fast and are finding reliable areas of applications.
The paper presents a novel learning-based framework to identify tables from scanned document images. The approach is designed as a structured labeling problem, which learns the layout of the document and labels its va...
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ISBN:
(纸本)1595930361
The paper presents a novel learning-based framework to identify tables from scanned document images. The approach is designed as a structured labeling problem, which learns the layout of the document and labels its various entities as table header, table trailer, table cell and non-table region. We develop features which encode the foreground block characteristics and the contextual information. These features are provided to a fixed point model which learns the inter-relationship between the blocks. The fixed point model attains a contraction mapping and provides a unique label to each block. We compare the results with Condition Random Fields(CRFs). Unlike CRFs, the fixed point model captures the context information in terms of the neighbourhood layout more efficiently. Experiments on the images picked from UW-III (University of Washington) dataset, UNLV dataset and our dataset consisting of document images with multi-column page layout, show the applicability of our algorithm in layout analysis and table detection. Copyright 2014 ACM.
作者:
C.S. SastryIT Bhawan
GEC Ranjhi PDPM Indian Institute of Information Technology Jabalpur Madhya Pradesh India
In several scientific areas, data are sampled irregularly and insufficiently due to practical and economical limitations. The use of such data in applications results in some artifacts and poor spatial resolution. The...
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In several scientific areas, data are sampled irregularly and insufficiently due to practical and economical limitations. The use of such data in applications results in some artifacts and poor spatial resolution. Therefore, before being used, the data are to be interpolated onto a regular grid. One of the methods achieving this objective is based on the Fourier reconstruction, which deals with the under-determined system of equations. The Stagewise Orthogonal Matching Pursuit (StOMP) is a recently proposed greedy algorithm. Compared to the other recent algorithms like l 1 - minimization techniques, StOMP admits certain promising features such as faster and simpler implementation even in large scale settings. The present work applies StOMP to the Fourier-based interpolation problem for the signals that have sparse Fourier spectra. The basic objective is to verify empirically the performance of the algorithm if, and how far, the measurement coordinates can be shifted from uniform distribution on the continuous interval. Taking kurtosis as a quantifier for the deviation of distribution from being uniform, we show numerically that the measurement coordinates can be significantly shifted from uniform distribution.
Communicating with a person having a hearing or speech disability is always a major challenge. Sign Language (SL) is a medium to remove the barrier of such type of communication. It is a very tough task for a common m...
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Web-based laboratories are promising to save the cost required to setup a hands-on laboratory in schools. There are several basic experiments in physics which help the students understand the basics of classical physi...
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ISBN:
(纸本)9781467385879
Web-based laboratories are promising to save the cost required to setup a hands-on laboratory in schools. There are several basic experiments in physics which help the students understand the basics of classical physics. However, the rising cost of laboratory infrastructure and costly equipment to conduct these experiments make it difficult for schools, in developing countries like India to build laboratories. This paper presents innovative web-based laboratory for physics to study equations of motion. One such experiment in equations of motion is the determination of acceleration due to gravity of a free falling object. However, measuring the distance traveled and time taken by a free-falling object is a tedious process. To overcome this challenge, a computervision based system is presented which can measure the distance traveled and time taken by the object during free fall. By the technique of object detection in computervision, the free-falling object is detected and tracked. The system is implemented using OpenCV libraries. The result of the analysis of free falling object is provided to the students through the web page.
Content Based image Retrieval (CBIR) techniques retrieve similar digital images from a large database. As the user often does not provide any clue (indication) of the region of interest in a query image, most methods ...
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ISBN:
(纸本)1595930361
Content Based image Retrieval (CBIR) techniques retrieve similar digital images from a large database. As the user often does not provide any clue (indication) of the region of interest in a query image, most methods of CBIR rely on a representation of the global content of the image. The desired content in an image is often localized (e.g. car appearing salient in a street) instead of being holistic, demanding the need for an object-centric CBIR. We propose a biologically inspired framework WOW ("What"Object is "Where") for this purpose. Design of WOW framework is motivated by the cognitive model of human visual perception and feature integration theory (FIT). The key contributions in the proposed approach are: (i) Feedback mechanism between Recognition ("What") and Localization ("Where") modules (both supervised), for a cohesive decision based on mutual consensus;(ii) Hierarchy of visual features (based on FIT) for an efficient recognition task. Integration of information from the two channels ("What" and "Where") in an iterative feedback mechanism, helps to filter erroneous contents in the outputs of individual modules. Finally, using a similarity criteria based on HOG features (spatially localized by WOW) for matching, our system effectively retrieves a set of rank-ordered samples from the gallery. Experimentation done on various real-life datasets (including PASCAL) exhibits the superior performance of the proposed method. Copyright 2014 ACM.
Automatic techniques to recognize and evaluate digital logic circuits are more efficient and require less human intervention, as compared to, traditional pen and paper methods. In this paper, we propose LEONARDO (Logi...
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