This volume contains nine papers, one of them nearly of monograph length (by L. Goldfarb), covering a broad range of topics in pattern recognition and computer vision. Three papers discuss the architectural and computational aspects of image processing and computer vision. The second trio of papers surveys three fundamental areas of vision: texture, shape and motion, while the final set of papers deals with pattern recognition theory, including classification rules and decision trees. The last paper presents a mathematical treatment of pattern recognition based on representing patterns in pseudoeuclidian vector spaces.
This volume contains nine papers, one of them nearly of monograph length (by L. Goldfarb), covering a broad range of topics in pattern recognition and computer vision. Three papers discuss the architectural and computational aspects of image processing and computer vision. The second trio of papers surveys three fundamental areas of vision: texture, shape and motion, while the final set of papers deals with pattern recognition theory, including classification rules and decision trees. The last paper presents a mathematical treatment of pattern recognition based on representing patterns in pseudoeuclidian vector spaces.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Maße
Höhe: 240 mm
Breite: 160 mm
ISBN-13
978-0-444-87723-9 (9780444877239)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Klassifikation
Image Processing Architectures: A Taxonomy and Survey (S. Yalamanchili et al.). Computational Models for Image Understanding (C. Guerra, S. Levialdi). Interactive Software Systems for Computer Vision (K. Voss, P. Hufnagl, R. Klette). Two-Dimensional Discrete Gaussian Markov Random Field Models for Image Processing (R. Chellappa). Recent Progress in Shape Decomposition and Analysis (L.G. Shapiro). Dynamic Scene Analysis (R. Jain). The Estimation of the Bayes Error by the k-Nearest Neighbor Approach (K. Fukunaga). Decision Trees in Pattern Recognition (G.R. Dattatreya, L.N. Kanal). A New Approach to Pattern Recognition (L. Goldfarb).
