correlation pattern recognition

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Correlation Pattern Recognition

Author : B. V. K. Vijaya Kumar
ISBN : 1139447122
Genre : Computers
File Size : 70. 47 MB
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Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target recognition, biometric recognition and optical character recognition. The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing. This 2005 book provides a needed review of this diverse background material and develops the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. It shows both digital and optical implementations. It also contains technology presented by the team that developed it and includes case studies of significant interest, such as face and fingerprint recognition. Suitable for graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.

Correlation Pattern Recognition

Author : B. V. K. Vijaya Kumar
ISBN : 0521153484
Genre : Computers
File Size : 30. 72 MB
Format : PDF
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Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target recognition, biometric recognition and optical character recognition. The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing. This 2005 book provides a needed review of this diverse background material and develops the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. It shows both digital and optical implementations. It also contains technology presented by the team that developed it and includes case studies of significant interest, such as face and fingerprint recognition. Suitable for graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.

Correlation Pattern Recognition

Author : B. V. K. Vijaya Kumar
ISBN : 0511136803
Genre : Correlation (Statistics)
File Size : 75. 3 MB
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A review of the background material needed for correlation pattern recognition for graduate students and practitioners.

Selected Papers On Optical Pattern Recognition Using Joint Transform Correlation

Author : Mohammad S. Alam
ISBN : UOM:39015041885891
Genre : Computers
File Size : 23. 60 MB
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SPIE Milestones are collections of seminal papers from the world literature covering important discoveries and developments in optics and photonics.

Advances In Structural And Syntactical Pattern Recognition

Author : Petra Perner
ISBN : 3540615776
Genre : Computers
File Size : 88. 75 MB
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This book constitutes the refereed proceedings of the 6th International Workshop on Structural and Syntactical Pattern Recognition, SSPR '96, held in Leipzig, Germany in August 1996. The 36 revised full papers included together with three invited papers were carefully selected from a total of 52 submissions. The papers are organized in topical sections on grammars and languages; morphology and mathematical approaches to pattern recognition; semantic nets, relational models and graph-based methods; 2D and 3D shape recognition; document image analysis and recognition; and handwritten and printed character recognition.

Pattern Recognition With Composite Correlation Filters Designed With Multi Object Combinatorial Optimization

Author :
ISBN : OCLC:957110229
Genre :
File Size : 67. 58 MB
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Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, for a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.

Machine Learning And Data Mining In Pattern Recognition

Author : Petra Perner
ISBN : 9783642030703
Genre : Computers
File Size : 76. 10 MB
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There is no royal road to science, and only those who do not dread the fatiguing climb of its steep paths have a chance of gaining its luminous summits. Karl Marx A Universial Genius of the 19th Century Many scientists from all over the world during the past two years since the MLDM 2007 have come along on the stony way to the sunny summit of science and have worked hard on new ideas and applications in the area of data mining in pattern r- ognition. Our thanks go to all those who took part in this year's MLDM. We appre- ate their submissions and the ideas shared with the Program Committee. We received over 205 submissions from all over the world to the International Conference on - chine Learning and Data Mining, MLDM 2009. The Program Committee carefully selected the best papers for this year’s program and gave detailed comments on each submitted paper. There were 63 papers selected for oral presentation and 17 papers for poster presentation. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data-mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining. Among these topics this year were special contributions to subtopics such as attribute discre- zation and data preparation, novelty and outlier detection, and distances and simila- ties.

Advances In Pattern Recognition

Author : Francesc J. Ferri
ISBN : 9783540679462
Genre : Computers
File Size : 55. 77 MB
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This book constitutes the joint refereed proceedings of the 8th International Workshop on Structural and Syntactic Pattern Recognition and the 3rd International Workshop on Statistical Techniques in Pattern Recognition, SSPR 2000 and SPR 2000, held in Alicante, Spain in August/September 2000. The 52 revised full papers presented together with five invited papers and 35 posters were carefully reviewed and selected from a total of 130 submissions. The book offers topical sections on hybrid and combined methods, document image analysis, grammar and language methods, structural matching, graph-based methods, shape analysis, clustering and density estimation, object recognition, general methodology, and feature extraction and selection.

Pattern Recognition

Author : Jose Francisco Martinez Trinidad
ISBN : 9783642215872
Genre : Computers
File Size : 32. 98 MB
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This book constitutes the refereed proceedings of the Third Mexican Conference on Pattern Recognition, MCPR 2011, held in Cancun, Mexico, in June/July 2011. The 37 revised full papers were carefully reviewed and selected from 69 submissions and are organized in topical sections on pattern recognition and data mining; computer vision and robotics; image processing; neural networks and signal processing; and natural language and document processing.

Analysis On Low Resolution Image Correlation Pattern Recognition Algorithm In Finite Space

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ISBN : OCLC:1027106562
Genre :
File Size : 74. 64 MB
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Abstract: Because traditional correlation pattern recognition algorithm cannot accurately identify low-resolution images, a low-resolution image correlation pattern recognition algorithm based on block-centric symmetric local binary model and weighted principal component analysis algorithm is proposed. Firstly, the feature of low-resolution image is extracted by using block CS-LBP operator. The weighted PCA operator is used to reduce the feature, and the classification feature is obtained. Secondly, the optimal classification class is selected by the nearest neighbor classifier, the recognition rate is calculated, and the whole algorithm is analyzed. Finally, the experiment is carried out. The experimental results showed that the algorithm has good recognition effect on ORL, and it is robust to the change of light and weather.

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