Artificial intelligence tools for pattern recognition

Elena Acevedo, Antonio Acevedo, Federico Felipe, Pedro Avilés

    Research output: Contribution to conferencePaper

    1 Scopus citations


    © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. 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.
    Original languageAmerican English
    StatePublished - 1 Jan 2017
    EventProceedings of SPIE - The International Society for Optical Engineering -
    Duration: 1 Jan 2017 → …


    ConferenceProceedings of SPIE - The International Society for Optical Engineering
    Period1/01/17 → …


    Dive into the research topics of 'Artificial intelligence tools for pattern recognition'. Together they form a unique fingerprint.

    Cite this