Selective color edge detector based on a neural classifier

Authors:
Horacio M. González Velasco;Carlos J. García Orellana;Miguel Macías Macías;Ramón Gallardo Caballero
Affiliations:
Department of Electronics and Electromechanical Engineering, University of Extremadura, Cáceres, Spain;Department of Electronics and Electromechanical Engineering, University of Extremadura, Cáceres, Spain;Department of Electronics and Electromechanical Engineering, University of Extremadura, Cáceres, Spain;Department of Electronics and Electromechanical Engineering, University of Extremadura, Cáceres, Spain
Venue:
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Year:
2005

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Abstract

Conventional edge detectors are not very useful for generating an edge map to be used in the search of a concrete object with deformable models or genetic algorithms. In this work, a selective color edge detector is presented, which is able to obtain the edges in the image and determine whether or not those edges are originated in a concrete object. The system is based on a multilayer perceptron neural network, which classifies the edges previously detected by the multidimensional gradient (color images), and is trained using some images of the searched object whose edges are known. The method has been successfully applied to bovine livestock images, obtaining edge maps to be used for a boundary extraction with genetic algorithms technique.