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Unsupervised texture image segmentation

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4 Author(s)
Mocofan, M. ; Politehnic Inst., Timisoara, Romania ; Caleanu, C. ; Lacrama, D. ; Alexa, F.

This paper is focused on a hierarchical structure of modular self-organizing neural networks for unsupervised texture segmentation (sofm-nn). Input data consists of local information regarding textures (cooccurrence matrix elements) and the texture image itself. An unsupervised segmentation is done using a sofm-nn network and then the final segmentation is performed by another sofm-nn neural network using the previously obtained results. Experimental results show the efficiency of the proposed method

Published in:

Neural Network Applications in Electrical Engineering, 2000. NEUREL 2000. Proceedings of the 5th Seminar on

Date of Conference:

2000