Recognizing Planar Objects Using Invariant Image Features

  • Editors
  • Thomas H. Reiss

Part of the Lecture Notes in Computer Science book series (LNCS, volume 676)

About this book


Given a familiar object extracted from its surroundings, we humans have little difficulty in recognizing it irrespective of its size, position and orientation in our field of view. Changes in lighting and the effects of perspective also pose no problems. How do we achieve this, and more importantly, how can we get a computer to do this? One very promising approach is to find mathematical functions of an object's image, or of an object's 3D description, that are invariant to the transformations caused by the object's motion. This book is devoted to the theory and practice of such invariant image features, so-called image invariants, for planar objects. It gives a comprehensive summary of the field, discussing methods for recognizing both occluded and partially occluded objects, and also contains a definitive treatmentof moment invariants and a tutorial introduction to algebraic invariants, which are fundamental to affine moment invariants and to many projective invariants. A number of novel invariant functions are presented and the results of numerous experiments investigating the stability of new and old invariants are discussed. The main conclusion is that moment invariants are very effective, both for partially occluded objects and for recognizing objects in grey-level images.


3D Affine Invarianten Affine Invariants Moment Objekterkennung Partial Occlusion Partielle Überdeckung Projective Invariants Projektive Invarianten algebra computer computer vision object recognition

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag 1993
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-56713-4
  • Online ISBN 978-3-540-47634-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book