SOM Segmentation of gray scale images for optical recognition

Authors:
Jesús Lázaro;Jagoba Arias;José L. Martín;Aitzol Zuloaga;Carlos Cuadrado
Affiliations:
Department of Electronics and Telecommunications. University of the Basque Country, Alameda Urquijo s/n, 48013 Bilbao, Spain;Department of Electronics and Telecommunications. University of the Basque Country, Alameda Urquijo s/n, 48013 Bilbao, Spain;Department of Electronics and Telecommunications. University of the Basque Country, Alameda Urquijo s/n, 48013 Bilbao, Spain;Department of Electronics and Telecommunications. University of the Basque Country, Alameda Urquijo s/n, 48013 Bilbao, Spain;Department of Electronics and Telecommunications. University of the Basque Country, Alameda Urquijo s/n, 48013 Bilbao, Spain
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

This paper describes a clustering technique using Self Organizing Maps and a two-dimensional histogram of the image. The two-dimensional histogram is found using the pixel value and the mean in the neighborhood. This histogram is fed to a self organizing map that divides the histogram into regions. Carefully selecting the number of regions, a scheme that allows an optimum optical recognition of texts can be found. The algorithm is specially suited for optical recognition application where a very high degree of confidence is needed. As an example application, the algorithm has been tested in a voting application, where a high degree of precision is required. Furthermore, the algorithm can be extended to any other thresholding or clustering applications.