A Hierarchic Method for Footprint Segmentation Based on SOM

Authors:
Marco Mora Cofre;Ruben Valenzuela;Girma Berhe
Affiliations:
Les Fous du Pixel Image Processing Research Group Department of Computer Science, Catholic University of Maule, Talca, Chile;Les Fous du Pixel Image Processing Research Group Department of Computer Science, Catholic University of Maule, Talca, Chile;Department of Computer Science, University of Luxembourg, Luxembourg L-1359
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Year:
2008

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Abstract

In this study we propose a new approach for solving the problem of segmenting the footprint in color images. Previous studies have presented direct and supervised methods for segmenting the footprint pattern. This new approach proposes, in comparison to the previous methods, a hierarchic segmentation method, the use of different color models to represent the image pixels, and the non-supervised classification based on SOM. The characteristics of the method allow a robust footprint segmentation with a high level of autonomy.