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Feature extraction using coordinate logic filters and Artificial Neural Networks

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5 Author(s)
Quintanilla-Dominguez, J. ; Grupo de Automatizacion de Senal y Comun., Univ. Politec. de Madrid, Madrid, Spain ; Sanchez-Garcia, M. ; Gozalez-Romo, M. ; Vega-Corona, A.
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This paper presents a novel feature extraction method using the combination of the Coordinate Logic Filters (CLF) and Artificial Neural Networks (ANN) applied to 2D signals (Images). The method consists of image enhancement by histogram adaptive equalization technique, features extraction by modifying gray levels applying a nonlinear adaptive transformation function and edge detection by Coordinate Logic Filters (CLF), generation, clustering and labelling of suboptimal features vectors by Self Organizing Map (SOM) Neural Network. For the detection we applied Back Propagation Neural Network (BPNN). This method is tested to detect Microcalcifications (MCs) in Regions of Interest (ROI) from mammograms. The experiment results show that the proposed method can locate MCs in an efficient way, moreover the method promise interesting advances in Medical Industry.

Published in:

Industrial Informatics, 2009. INDIN 2009. 7th IEEE International Conference on

Date of Conference:

23-26 June 2009

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