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Computer analysis of images and patterns : 9th international conference, CAIP 2001, Warsaw, Poland, September 5-7, 2001 : proceedings

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Computer analysis of images and patterns : 9th international conference, CAIP 2001, Warsaw, Poland, September

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Author: CAIP 2001 (2001 : Warsaw, Poland), Skarbek, Władysław

Added by: sketch

Added Date: 2015-12-30

Language: eng

Subjects: Image processing, Computer vision, Optical pattern recognition

Publishers: Berlin ; New York : Springer

Collections: folkscanomy miscellaneous, folkscanomy, additional collections

ISBN Number: 3540425136

Pages Count: 300

PPI Count: 300

PDF Count: 1

Total Size: 362.20 MB

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Computer Analysis of Images and Patterns: 9th International Conference, CAIP 2001 Warsaw, Poland, September 5–7, 2001 Proceedings
Author: Władysław Skarbek
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-42513-7
DOI: 10.1007/3-540-44692-3

Table of Contents:

  • MPEG-7: Evolution or Revolution?
  • The MPEG-7 Visual Description Framework — Concepts, Accuracy, and Applications
  • MPEG-7 Color Descriptors and Their Applications
  • Texture Descriptors in MPEG-7
  • An Overview of MPEG-7 Motion Descriptors and Their Applications
  • MPEG-7 MDS Content Description Tools and Applications
  • Image Retrieval Using Spatial Color Information
  • Lifting-Based Reversible Transforms for Lossy-to-Lossless Wavelet Codecs
  • Coding of Irregular Image Regions by SA DFT
  • Fast PNN Using Partial Distortion Search
  • Near-Lossless Color Image Compression with No Error Accumulation in Multiple Coding Cycles
  • Hybrid Lossless Coder of Medical Images with Statistical Data Modelling
  • A Simple Algorithm for Ordering and Compression of Vector Codebooks
  • MPEG 2-Based Video Coding with Three-Layer Mixed Scalability
  • The Coefficient Based Rate Distortion Model for the Low Bit Rate Video Coding
  • Shape-Adaptive DCT Algorithm — Hardware Optimized Redesign
  • Superquadric-Based Object Recognition
  • Weighted Graph-Matching Using Modal Clusters
  • Discovering Shape Categories by Clustering Shock Trees
  • Feature Selection for Classification Using Genetic Algorithms with a Novel Encoding

Includes bibliographical references and index

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