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Cellular learning automata-based color image segmentation using adaptive chains

Abin, A. A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/CSICC.2009.5349621
  3. Abstract:
  4. This paper presents a new segmentation method for color images. It relies on soft and hard segmentation processes. In the soft segmentation process, a cellular learning automata analyzes the input image and closes together the pixels that are enclosed in each region to generate a soft segmented image. Adjacency and texture information are encountered in the soft segmentation stage. Soft segmented image is then fed to the hard segmentation process to generate the final segmentation result. As the proposed method is based on CLA it can adapt to its environment after some iterations. This adaptive behavior leads to a semi content-based segmentation process that performs well even in presence of noise. Experimental results show the effectiveness of the proposed segmentation method. ©2009 IEEE
  5. Keywords:
  6. Adaptive behavior ; Cellular learning automata ; Color image segmentation ; Color images ; Content-based segmentation ; Input image ; Segmentation methods ; Segmentation process ; Segmentation results ; Segmented images ; Texture information ; Image segmentation ; Translation (languages) ; Automata theory
  7. Source: 2009 14th International CSI Computer Conference, CSICC 2009, 20 October 2009 through 21 October 2009, Tehran ; 2009 , Pages 452-457 ; 9781424442621 (ISBN)
  8. URL: http://ieeexplore.ieee.org/document/5349621