Artificial intelligence tools for pattern recognition

Elena Acevedo; Antonio Acevedo; Federico Felipe; Pedro Avilés

doi:10.1117/12.2280310

19 June 2017 Artificial intelligence tools for pattern recognition

Elena Acevedo, Antonio Acevedo, Federico Felipe, Pedro Avilés

Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 1044302 (2017) https://doi.org/10.1117/12.2280310
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore

Abstract

In this work, we present a system for pattern recognition that combines the power of genetic algorithms for solving problems and the efficiency of the morphological associative memories. We use a set of 48 tire prints divided into 8 brands of tires. The images have dimensions of 200 x 200 pixels. We applied Hough transform to obtain lines as main features. The number of lines obtained is 449. The genetic algorithm reduces the number of features to ten suitable lines that give thus the 100% of recognition. Morphological associative memories were used as evaluation function. The selection algorithms were Tournament and Roulette wheel. For reproduction, we applied one-point, two-point and uniform crossover.

Citation Download Citation

Elena Acevedo, Antonio Acevedo, Federico Felipe, and Pedro Avilés "Artificial intelligence tools for pattern recognition", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 1044302 (19 June 2017); https://doi.org/10.1117/12.2280310

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