Hardware Implementation of Image Recognition System Based on Morphological Associative Memories and Discrete Wavelet Transform

  • Enrique Guzmán
  • Selene Alvarado
  • Oleksiy Pogrebnyak
  • Luis Pastor Sánchez Fernández
  • Cornelio Yañez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4872)

Abstract

The implementation of a specific image recognition technique for an artificial vision system is presented. The proposed algorithm involves two steps. First, smaller images are obtained using Discrete Wavelet Transform (DWT) after four stages of decomposition and taking only the approximations. This way the volume of information to process is reduced considerably and the system memory requirements are reduced as well. Another purpose of DWT is to filter noise that could be induced in the images. Second, the Morphological Associative Memories (MAM) are used to recognize landmarks. The proposed algorithm provides flexibility, possibility to parallelize algorithms and high overall performance of hardware implemented image retrieval system. The resulted hardware implementation has low memory requirements, needs in limited arithmetical precision and reduced number of simple operations. These benefits are guaranteed due to the simplicity of MAM learning/restoration process that uses simple morphological operations, dilation and erosion, in other words, MAM calculate maximums or minimums of sums. These features turn out the artificial vision system to be robust and optimal for the use in realtime autonomous systems. The proposed image recognition system has, among others, the following useful features: robustness to the noise induced in the patter to process, high processing speed, and it can be easily adapted to diverse operation circumstances.

Keywords

Artificial Vision Image Recognition Morphological Associative Memories Discrete Wavelet Transform Hardware Implementation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Enrique Guzmán
    • 1
  • Selene Alvarado
    • 1
  • Oleksiy Pogrebnyak
    • 2
  • Luis Pastor Sánchez Fernández
    • 2
  • Cornelio Yañez
    • 2
  1. 1.Universidad Tecnológica de la Mixteca 
  2. 2.Centro de Investigación en Computación del Instituto Politécnico Nacional 

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