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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 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 state-of-the-art technology presented by the team that developed it and includes case studies of significant current interest, such as face and fingerprint recognition. Suitable for advanced undergraduate or graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.

Correlation (Statistics). --- Pattern recognition systems.

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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.

Pattern recognition systems. --- Correlation (Statistics)

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CIARP 2005 (10th Iberoamerican Congress on Pattern Recognition, X CIARP) is the 10th event in the series of pioneer congresses on pattern recognition in the Iberoamerican community, which takes place in La Habana, Cuba. As in previous years, X CIARP brought together international scientists to promote and disseminate ongoing research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis, and natural language processing and recognition, to name a few. Moreover, X CIARP was a forum for scientific research, experience exchange, share of new knowledge and increase in cooperation between research groups in pattern recognition, computer vision and related areas. The 10th Iberoamerican Congress on Pattern Recognition was organized by the Cuban Association for Pattern Recognition (ACRP) and sponsored by the Institute of Cybernetics, Mathematics and Physics (ICIMAF), the Advanced Technologies Application Center (CENATAV), the University of Oriente (UO), the Polytechnic Institute “José A Echevarria” (ISPJAE), the Central University of Las Villas (UCLV), the Ciego de Avila University (UNICA), as well as the Center of Technologies Research on Information and Systems (CITIS-UAEH) in Mexico. The conference was also co-sponsored by the Portuguese Association for Pattern Recognition (APRP), the Spanish Association for Pattern Recognition and Image Analysis (AERFAI), the Special Interest Group of the Brazilian Computer Society (SIGPR-SBC), and the Mexican Association for Computer Vision, Neurocomputing and Robotics (MACVNR). X CIARP was endorsed by the International Association for Pattern Recognition (IAPR).

Pattern recognition. --- Optical data processing. --- Artificial intelligence. --- Pattern Recognition. --- Image Processing and Computer Vision. --- Artificial Intelligence. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Pattern recognition systems --- Image processing

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This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition. Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and in

Pattern perception. --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception

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ICIAR 2005, the International Conference on Image Analysis and Recognition, was the second ICIAR conference, and was held in Toronto, Canada. ICIAR is organized annually, and alternates between Europe and North America. ICIAR 2004 was held in Porto, Portugal. The idea of o?ering these conferences came as a result of discussion between researchers in Portugal and Canada to encourage collaboration and exchange, mainly between these two countries, but also with the open participation of other countries, addressing recent advances in theory, methodology and applications. TheresponsetothecallforpapersforICIAR2005wasencouraging.From295 full papers submitted, 153 were ?nally accepted (80 oral presentations, and 73 posters). The review process was carried out by the Program Committee m- bersandotherreviewers;allareexpertsinvariousimageanalysisandrecognition areas. Each paper was reviewed by at least two reviewers, and also checked by the conference co-chairs. The high quality of the papers in these proceedings is attributed ?rst to the authors,and second to the quality of the reviews provided by the experts. We would like to thank the authors for responding to our call, andwewholeheartedlythankthe reviewersfor theirexcellentwork,andfortheir timely response. It is this collective e?ort that resulted in the strong conference program and high-quality proceedings in your hands.

Pattern recognition. --- Application software. --- Optical data processing. --- Artificial intelligence. --- Computer graphics. --- Pattern Recognition. --- Computer Applications. --- Image Processing and Computer Vision. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Artificial Intelligence. --- Computer Graphics. --- Image analysis --- Optical pattern recognition