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Image Pattern Recognition

  • V. A. Kovalevsky

Table of contents

  1. Front Matter
    Pages i-xi
  2. V. A. Kovalevsky
    Pages 1-39
  3. V. A. Kovalevsky
    Pages 57-66
  4. V. A. Kovalevsky
    Pages 91-116
  5. V. A. Kovalevsky
    Pages 145-176
  6. V. A. Kovalevsky
    Pages 177-198
  7. V. A. Kovalevsky
    Pages 199-227
  8. Back Matter
    Pages 228-241

About this book

Introduction

During the last twenty years the problem of pattern recognition (specifically, image recognition) has been studied intensively by many investigators, yet it is far from being solved. The number of publications increases yearly, but all the experimental results-with the possible exception of some dealing with recognition of printed characters-report a probability of error significantly higher than that reported for the same images by humans. It is widely agreed that ideally the recognition problem could be thought of as a problem in testing statistical hypotheses. However, in most applications the immediate use of even the simplest statistical device runs head on into grave computational difficulties, which cannot be eliminated by recourse to general theory. We must accept the fact that it is impossible to build a universal machine which can learn an arbitrary classification of multidimensional signals. Therefore the solution of the recognition problem must be based on a priori postulates (concerning the sets of signals to be recognized) that will narrow the set of possible classifications, i.e., the set of decision functions. This notion can be taken as the methodological basis for the approach adopted in this book.

Keywords

Mustererkennung algorithms classification noise pattern pattern recognition

Authors and affiliations

  • V. A. Kovalevsky
    • 1
  1. 1.Institute of CyberneticsAcademy of Sciences of the Ukranian SSRKievUSSR

Bibliographic information