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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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Chart classification: An empirical comparative study of different learning models 21

Chart classification: An empirical comparative study of diff...

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12th indian conference on computer vision, graphics and image processing, ICVGIP 2021

作者： Thiyam, Jennil Singh, Sanasam Ranbir Bora, Prabin K. IIT Guwahati India

ISBN: (纸本)9781450391276

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 documents with various chart types, chart classification has become an important task for downstream applications such as chart data recovery, chart replenishment, etc. Though there have been various studies reported in the literature on chart classification using different classification methods, three of the important concerns are small dataset size, a small number of chart types, and inconsistencies in the performance reported in different studies. Motivated by the above concerns, this paper curates a large dataset of real chart images (110k samples) with a large number of chart types (24 charts types) and evaluates 21 different machine learning models. To the best of our knowledge, this is the largest (in sample size and chart types) real chart dataset reported in the literature to date. We further study - (i) the effect of dataset size on the classification model, (ii) the nature of chart noises and their influences on classification performance, and (iii) confusing chart pairs leading to misclassification. © 2021 ACM.

关键词： image classification

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Adaptive Nonlinear image Denoising and Restoration Using a Cooperative Bayesian Estimation Approach

Adaptive Nonlinear Image Denoising and Restoration Using a C...

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

作者： Akshaya. K. Mishra Alexander Wong David. A. Clausi Paul. W. Fieguth

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.

关键词： image denoising image restoration Bayesian methods Signal to noise ratio Noise reduction Degradation Discrete wavelet transforms PSNR Noise shaping Filtering

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Homomorphic incremental directional averaging for noise suppression in SAR images 6th

Homomorphic incremental directional averaging for noise supp...

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

作者： Aswatha, Shashaank M. Mukhopadhyay, Jayanta Biswas, Prabir K. Aikat, Subhas Indian Institute Technology Kharagpur KharagpurWest Bengal721 302 India

ISBN: (纸本)9789811300196

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 multiplicative noise, particularly in single-look-complex (SLC) mode. There are extensive works in the literature for denoising SAR data, which are usually applied on amplitude data, or on coherency/covariance data. In this paper, we propose a two-channel filtering technique for noise suppression in complex SAR data. The rectangular format of complex SAR data is represented in phasor form to execute noise filtering over amplitude and phase independently, and then converted back to the rectangular format for subsequent applications. In this approach, it is observed that, the surface texture information is visibly retained while suppressing the noise considerably well, in comparison to reference multi-look image. As an application, we show the advantage of proposed noise suppression technique in classification of SAR images. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Synthetic aperture radar

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MANUFACTURING METROLOGY PRESENT STATUS - FUTURE PROSPECTS.

MANUFACTURING METROLOGY PRESENT STATUS - FUTURE PROSPECTS.

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Emerging Trends in Manufacturing: proceedings of the 12th All India Machine Tool Design and Research conference.

作者： Radhakrishnan, V. Indian Inst of Technology Madras India Indian Inst of Technology Madras India

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, computer vision and image processing techniques etc. are developing fast and are finding reliable areas of applications.

关键词： MEASUREMENTS

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Table extraction from document images using fixed point model 14

Table extraction from document images using fixed point mode...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Bansal, Anukriti Harit, Gaurav Dutta Roy, Sumantra IIT Delhi India IIT Jodhpur India

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.

关键词： image analysis

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Regularization of Incompletely, Irregularly and Randomly Sampled Data

Regularization of Incompletely, Irregularly and Randomly Sam...

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

作者： C.S. Sastry IT 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. 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.

关键词： Matching pursuit algorithms Signal processing algorithms Interpolation Coordinate measuring machines Geophysical measurements image reconstruction Equations Large-scale systems Seismic measurements computer vision

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Artificial Intelligence based indian Sign Language Recognition with Accelerated Performance under HPC Environment 20

Artificial Intelligence based Indian Sign Language Recogniti...

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20th OITS International conference on Information Technology, OCIT 2022

作者： Panigrahi, Niranjan Parala Maharaja Engineering College Center of Excellence High Performance Computing Lab Department of Cse Odisha Berhampur India

ISBN: (纸本)9781665493482

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 man to understand SL and interprets its meaning. So, an automated system is necessary which can recognize the SL characters and display its meaning and semantics. In this context, this article has presented a systematic investigation of Artificial Intelligence (AI) based approaches towards examining the difficulties in the classification of characters in indian Sign Language (ISL). In this work, we adapted ISL recognition using computer vision, Machine Learning and Deep Learning methodologies. To achieve this requirement, the captured image undergoes a series of pre-processing steps which include various computer vision techniques such as conversion to gray-scale and thresholding using OTSU algorithm. Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and pre-trained models, VGG-19 and Inception-V3using Transfer Learning mechanism are used to train the system. Further, due to large image dataset, the training time of the models are also accelerated using PARAM SHAVAK HPC system which shows a reasonable improvement in the performance of the models. © 2022 IEEE.

关键词： Semantics

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Web-Based Physics Experiments in Dynamics Using image processing 1

Web-Based Physics Experiments in Dynamics Using Image Proces...

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1st IEEE International conference on Power Electronics, Intelligent Control, and Energy Systems (ICPEICES)

作者： Pattanashetty, Kiran C. Kumar, Ranjeet Pandian, S. R. Indian Inst Informat Technol Design & Mfg Kanchee Dept Elect Engn Madras Tamil Nadu India

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 computer vision 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 computer vision, 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.

关键词： OpenCV Object Detection Acceleration Due to Gravity Dynamics Experiment

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Revealing what to extract from where, for object-centric content based image retrieval (CBIR) 14

Revealing what to extract from where, for object-centric con...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Gupta, Nitin Das, Sukhendu Chakraborti, Sutanu Dept. of CS and E IIT Madras India

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.

关键词： Iterative methods

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Automatic synthesis of boolean expression and error detection from logic circuit sketches 6th

Automatic synthesis of boolean expression and error detectio...

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

作者： Dhiman, Sahil Garg, Pushpinder Sharma, Divya Chattopadhyay, Chiranjoy Indian Institute of Technology Jodhpur JodhpurRajasthan India

ISBN: (纸本)9789811300196

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 (Logic Expression fOrmatioN And eRror Detection framewOrk), a hierarchical approach to recognize boolean expression from hand drawn digital logic gate diagram. The key contributions in the proposed approach are: (i) a novel hierarchical framework to synthesize boolean expression from a hand drawn logic circuit diagram;and (ii) identification of anomalies in drawing. Extensive experimentation was performed through qualitative and quantitative analysis. Results were also compared with existing techniques proposed on the similar problem. Upon experimentation and analysis, our system proved to be more robust to user variability in design and yielded an accuracy of 95.2 %, which is a 4 % gain over others. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Error detection

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