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.
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Mora Cofre, M., Valenzuela, R., Berhe, G. (2008). A Hierarchic Method for Footprint Segmentation Based on SOM. In: Kůrková, V., Neruda, R., KoutnÃk, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87536-9_91
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DOI: https://doi.org/10.1007/978-3-540-87536-9_91
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