This paper presents the design of a machine vision based system for real time detection of the counterfeit Bangladeshi bank notes. The proposed system works with the denominations of five hundred and one hundred taka....
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ISBN:
(纸本)1424415500;1424415519
This paper presents the design of a machine vision based system for real time detection of the counterfeit Bangladeshi bank notes. The proposed system works with the denominations of five hundred and one hundred taka. This system relies on a specific feature of the both five hundred and one hundred taka. The relied feature is not possible to replicate for the counterfeit makers or producers. And there is no foreseeable likelihood that they would be capable to imitate this feature even within a pretty long time. The relied feature is the repeatedly printed ldquoBANGLADESHBANKrdquo on some portions of the notes using microprint technique. The proposed stand alone system captures the portions of the notes with a proprietary scanner called the Grid Scanner [1]. The captured image is then processed by a microcontroller PIC-16F648A or ATMega88 (AVR). The microcontroller then determines the validity of the note based on an OCR technique by looking for the characters dasiaBpsila, dasiaApsila and dasiaNpsila in the scanned image. The success-rate of the counterfeit detection with properly captured image is 100% and the average processing time is 250 milliseconds with above mentioned microcontroller.
Commercial products that support L2-learners with computer assisted pronunciation training usually focus per exercise only on one possible pronunciation mistake that is typical for speakers of the respective L1 group....
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Commercial products that support L2-learners with computer assisted pronunciation training usually focus per exercise only on one possible pronunciation mistake that is typical for speakers of the respective L1 group. Acoustic models for words with wrong pronunciation are added to the system. In the present paper a more general approach with features that have proved to be widely independent of the learners' mother tongue is proposed. It is able to take various possible mistakes into consideration all at once. High dimensional feature vectors that encode prosodic varieties and differences of reference and recognized sentences are analyzed. With the ADABOOST algorithm those features are found, which contain the most important information to assess German children learning English. With 35 features 89 % of the agreement of experts is achieved.
Wide baseline matching is the state of the art for object recognition and image registration problems in computervision. Though effective, the computational expense of these algorithms limits their application to man...
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Wide baseline matching is the state of the art for object recognition and image registration problems in computervision. Though effective, the computational expense of these algorithms limits their application to many real-world problems. The performance of wide baseline matching algorithms may be improved by using a graphical processing unit as a fast multithreaded co-processor. In this paper, we present an implementation of the difference of Gaussian feature extractor, based on the CUDA system of GPU programming developed by NVIDIA, and implemented on their hardware. For a 2000x2000 pixel image, the GPU-based method executes nearly thirteen times faster than a comparable CPU-based method, with no significant loss of accuracy.
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and com...
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ISBN:
(数字)9783642040702
ISBN:
(纸本)9783642040696
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring - gether researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the multifaceted aspects of intelligent computing. ICIC 2009, held in Ulsan, Korea, September 16–19, 2009, constituted the 5th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005 held in Shanghai, Qingdao, Kunming, and Hefei, China, 2008, 2007, 2006, and 2005, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the p- ture of contemporary intelligent computing techniques as an integral concept that hi- lights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Emerging Intelligent Computing Technology and Applications.” Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
发现在二幅图象之间的可靠的相应的点是在计算机视觉的一个基本问题，特别与 L 视觉框架的发展。这篇论文介绍歧管的通讯并且建议一个新奇计划由听说向上的看法拒绝孤立点歧管。建议计划独立于在出版工作要估计并且克服可得到的方法的...
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发现在二幅图象之间的可靠的相应的点是在计算机视觉的一个基本问题，特别与 L 视觉框架的发展。这篇论文介绍歧管的通讯并且建议一个新奇计划由听说向上的看法拒绝孤立点歧管。建议计划独立于在出版工作要估计并且克服可得到的方法的下列限制的参量的模型：效率严厉地因孤立点百分比的增加和估计的模型参数的数字倒下；孤立点拒绝被结合模型选择和模型评价。真实图象对的实验显示出我们的建议计划的优秀性能。
Instead of traditionally using a 3D physical model with many control points on it, a calibration plate with printed chess grid and movable along its normal direction is implemented to provide large area 3D control poi...
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Instead of traditionally using a 3D physical model with many control points on it, a calibration plate with printed chess grid and movable along its normal direction is implemented to provide large area 3D control points with variable Z values. Experiments show that the approach presented is effective for reconstructing 3D color objects in computervision system.
Three different localized representation methods and a manifold learning approach to face recognition are compared in terms of recognition accuracy. The techniques under investigation are (a) local nonnegative matrix ...
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Three different localized representation methods and a manifold learning approach to face recognition are compared in terms of recognition accuracy. The techniques under investigation are (a) local nonnegative matrix factorization (LNMF);(b) independent component analysis (ICA);(c) NMF with sparse constraints (NMFsc);(d) locality-preserving projections (Laplacian faces). A systematic comparative analysis is conducted in terms of distance metric used, number of selected features, and sources of variability on AR and Olivetti face databases. Results indicate that the relative ranking of the methods is highly task-dependent, and the performances vary significantly upon the distance metric used. Copyright (C) 2007 I. B. Ciocoiu and H. N. Costin.
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