Handbook of pattern recognition & computer vision
著者
書誌事項
Handbook of pattern recognition & computer vision
World Scientific, c1993
大学図書館所蔵 全35件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Pattern recognition and computer vision and their applications have experienced enormous progress in research and development over the last two decades. This comprehensive handbook, with chapters by leading experts in their fields, documents both the basics and new and advanced results.The book gives the most total treatment of basic methods in pattern recognition including statistical, neurocomputing, syntactic/structural/grammatical approaches, feature selection and cluster analysis; and an extensive presentation of basic methods in computer vision including texture analysis and models, color, geometrical tools, image sequence analysis, etc. Major and unique applications are also covered, such as food handling using computer vision, non-destructive evaluation of materials, applications in economics and business, medical image recognition and understanding, etc. Broader system aspects are also examined, including optical pattern recognition and architectures for computer vision.Researchers, students and users of pattern recognition and computer vision will find the book an essential reference tool. The volume is also an invaluable collection of basic techniques and principles, which would otherwise be hard to assemble, in one convenient volume.
目次
- Part 1 Basic methods in pattern recognition: statistical pattern recognition, K. Fukunaga
- large-scale feature selection, J. Sklansky and W. Siedlecki. Part 2 Basic method in image processing and vision: vision engineering - designing computer vision systems, R. Chellapa and A. Rosenfeld
- colour in computer vision, Q-T. Luong
- model-based texture segmentation, R. Chellapa et al
- positional estimation techniques for an autonomous mobile robot - a review, R. Talluri and J.K. Aggarwal. Part 3 Recognition applications: pattern recognition in geophysical signal processing and interpretation, Y. Li et al
- optical handwritten Chinese character recognition, J.S. Huang. Part 4 Inspection and robotic applications: computer vision in food handling and sorting, H. Arnason and M. Asmundsson
- quantitative 3-D methods in medical imaging, M. Loew. Part 5 Architectures and technology: optical pattern recognition for computer vision, D. Casasent
- connectionist architectures in low-level image segmentation, W. Blanz and S. Gish.
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