Pictorial Data Analysis. Proceedings of the NATO Advanced Study Insititut on Pictorial Data Analysis at de Bonas, France, August 1-12, 1982). (= NATO ASI Series, Series F: Computer and Systems Sciences, Volume 4).

Haralick, Robert M. (Editor):

ISBN 10: 3540122885 / ISBN 13: 9783540122883

Published by Springer, Berlin / Heidelberg / New York / Tokyo, 1983

About this Item

VIII, 468 S. mit zahlreichen Abbildungen, 3540122885 Sprache: Deutsch Gewicht in Gramm: 1010 Groß 8°, Original-Pappband (Hardcover), Bibliotheks-Exemplar (ordnungsgemäß entwidmet) mit leichten Kleberückständen vom Rückenschild, Stempel auf Titel, insgesamt gutes und innen sauberes Exemplar, (library copy in good condition),

Seller Inventory # 80980

Bibliographic Details

• Title: Pictorial Data Analysis. Proceedings of the NATO Advanced Study Insititut on Pictorial Data Analysis at de Bonas, France, August 1-12, 1982). (= NATO ASI Series, Series F: Computer and Systems Sciences, Volume 4).
• Publisher: Springer, Berlin / Heidelberg / New York / Tokyo
• Publication Date: 1983
• Language: German
• ISBN 10: 3540122885
• ISBN 13: 9783540122883
• Binding: Hardcover
• Weight: 1010 grams
• Seller catalogs:
  • Mathematik

About this title

Synopsis

This volume is the collection of lectures and presentations of the NATO AS! On Pictorial Data Analysis, held August 1-12, 1982 in the beautiful chateau de Bonas, Bonas France. The director of the AS! was Robert M. Haralick and the Co-director was Stefano Levialdi. The papers in the book are arranged in two sections first theory and general prinicples and then applications. Local computations play a central role in image processing both when a traditional computer is used and when parallel machines are used for improving image throughput. Levialdi reviews such neighborhood operators. Hung and Kasvand discuss a line thinning application which involves detection of critical points on chain encoded data. Most low level image processing has been done using the digital raster as the basic data structure. Within the last few years many of these basic algorithms have been developed for the quadtree data structure. The quadtree permits easier access to certain kinds of spatial adjacency relationships in a variable resolution context. Rosenfeld reviews the properties of these representations and their uses in image segmentation and property measurement. Besslich discusses an expanded form of an invertible quadtree representation which permits a multiprocessor execution. Gisolfi and Vitulano discuss the C-matrix and C-filtering technique for image and texture feature extraction. O'mara et.al. discuss the application of Codel numbers to image feature extraction. Kropatsch discusses an image segmentation technique which permits the effective use of a variety of different kinds of segmentation techniques.