Wavelets for multiresolution shape recognition

  • Maria Grazia Albanesi
  • Luca Lombardi
Poster Session C: Compression, Hardware & Software, Image Databases, Neural Networks, Object Recognition & Reconstruction
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)

Abstract

This paper describes a new method for 2-D shape recognition based on a multiresolution characterisation of the shape. From the Wavelet coefficients, features are extracted in order to perform a translation-rotation-scaling invariant recognition. Wavelets and multiresolution are exploited in order to reduce complexity of the matching task between the input image and the set of models. In the paper, motivations and performance of the algorithm are presented. Experimental results are also reported in several tests, including noise addition. The approach is quite general, and it could be extended to texture analysis, thus providing a unified paradigm for shape and texture recognition.

Keywords

Input Image Recognition Task Wavelet Transform Wavelet Coefficient Shape Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Maria Grazia Albanesi
    • 1
  • Luca Lombardi
    • 1
  1. 1.Dipartimento di Informatica e SistemisticaUniversity of PaviaPaviaItaly

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