Resumen

MUNOZ-NEIRA, Milton Javier et al. Design of a pattern recognition system in thermographic and footprint images for flatfoot identification in children between five and six years old. Rev. Cient. [online]. 2019, n.36, pp.313-324. ISSN 0124-2253.  https://doi.org/10.14483/23448350.14345.

The following paper presents the main results of exploratory research oriented to the design and implementation of a pattern recognition system for flatfoot identification in children between 5 and 6 years. Patterns were determined from texture analysis of foot thermographic images, and from contour analysis of footprint images. For each case, an artificial neuronal network was trained, with base in a back-propagation algorithm. In each trial, 70 % of data were used for training, and 30 % for validation. For experiments done, success rates greater than 80 % were achieved. The best results were reached with contour patterns reduced by principal components analysis, PCA, in a binary system, with a success rate of 90.84 % in cross-validation. Results are a contribution to the study of diagnostic techniques for flatfoot treatment through the use of technologic tools.

Palabras clave : artificial neuronal networks; flatfoot; footprint patterns; texture patterns..

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