@inproceedings{92514c5a867a48ada498ec0e8ec6e1c5,
title = "Artificial intelligence tools for pattern recognition",
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.",
keywords = "Artificial Intelligence, Associative memories, Feature selection, Genetic algorithm, Hough transform, Morphological operators, Pattern recognition, Tire prints",
author = "Elena Acevedo and Antonio Acevedo and Federico Felipe and Pedro Avil{\'e}s",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; 2nd International Workshop on Pattern Recognition, IWPR 2017 ; Conference date: 01-05-2017 Through 03-05-2017",
year = "2017",
doi = "10.1117/12.2280310",
language = "Ingl{\'e}s",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Guojian Chen and Xudong Jiang and Masayuki Arai",
booktitle = "Second International Workshop on Pattern Recognition",
address = "Estados Unidos",
}