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Neural based binarization techniques

Hatem Hamza 1 Eddie Smigiel 2 Abdel Belaïd 1
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LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
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.
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https://hal.inria.fr/inria-00000359
Contributor : Hatem Hamza <>
Submitted on : Tuesday, September 27, 2005 - 3:10:31 PM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM

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  • HAL Id : inria-00000359, version 1

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Hatem Hamza, Eddie Smigiel, Abdel Belaïd. Neural based binarization techniques. 8th International Confrence on Document Analysis and Recognition - ICDAR'05, Aug 2005, Seoul/Korea. ⟨inria-00000359⟩

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