Feature Extraction of Postage Stamps Using an Iterative Approach of CNN

Jun KISHIDA  Csaba REKECZKY  Yoshifumi NISHIO  Akio USHIDA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E79-A   No.10   pp.1741-1746
Publication Date: 1996/10/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Neural Networks
Keyword: 
cellular neural networks,  analogic algorithm,  image processing,  feature extraction,  gradient controlled diffusion,  

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Summary: 
In this article, a new analogic CNN algorithm to extract features of postage stamps in gray-scale images Is introduced. The Gradient Controlled Diffusion method plays an important role in the approach. In our algorithm, it is used for smoothing and separating Arabic figures drawn with a color which is similar to the background color. We extract Arabic figures in postage stamps by combining Gradient Controlled Diffusion with nearest neighbor linear CNN template and logic operations. Applying the feature extraction algorithm to different test images it has been verified that it is also effective in complex segmentation problems