A Filter of Concentric Shapes for Image Recognition and Its Implementation in a Modified DT-CNN

Hector SANDOVAL  Taizoh HATTORI  Sachiko KITAGAWA  Yasutami CHIGUSA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E84-A   No.9   pp.2189-2197
Publication Date: 2001/09/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)
Category: Image & Signal Processing
edge detection,  recursive thinning,  cellular neural networks,  image processing,  

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This paper describes the implementation of a proposed image filter into a Discrete-Time Cellular Neural Network (DT-CNN). The three stages that compose the filter are described, showing that the resultant filter is capable of (1) erasing or detecting several concentric shapes simultaneously, (2) thresholding and (3) thinning of gray-scale images. Because the DT-CNN has to fill certain conditions for this filter to be implemented, it becomes a modified version of a DT-CNN. Those conditions are described and also experimental results are clearly shown.