SOM Segmentation of gray scale images for optical recognition

被引:15
作者
Lazaro, Jesus [1 ]
Arias, Jagoba [1 ]
Martin, Jose L. [1 ]
Zuloaga, Aitzol [1 ]
Cuadrado, Carlos [1 ]
机构
[1] Univ Basque Country, Dept Elect & Telecommun, Bilbao 48013, Spain
关键词
thresholding; clustering; self organizing map;
D O I
10.1016/j.patrec.2006.06.011
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1991 / 1997
页数:7
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