Title :
Neural based binarization techniques
Author :
Hamza, Hatem ; Smigiel, Eddie ; Belaid, Abdel
Author_Institution :
LORIA, Univ. Nancy 2, France
fDate :
29 Aug.-1 Sept. 2005
Abstract :
This paper introduces three neural based binarization techniques. These techniques start with a self organizing map (SOM) applied on the image to extract its most representative grey levels or colors. The classification goes further in two different ways. In the case of grey level images, the Kmeans algorithm or Sauvola´s or Niblack´s thresholds are used, whereas a multi layer perceptron (MLP) is used in the case of color images. The obtained results are discussed and we show that they are better than those of some classical binarization techniques.
Keywords :
image classification; image colour analysis; image segmentation; multilayer perceptrons; self-organising feature maps; Kmeans algorithm; Sauvola threshold; color images; grey level images; multilayer perceptron; neural based binarization technique; self organizing map; Color; Computer vision; Entropy; Histograms; Image processing; Image recognition; Neurons; Pattern recognition; Self organizing feature maps; Text recognition;
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
Print_ISBN :
0-7695-2420-6
DOI :
10.1109/ICDAR.2005.168