Edge Detection in Noisy Images Using the Support Vector Machines

Authors:
Hilario Gómez-Moreno;Saturnino Maldonado-Bascón;Francisco López-Ferreras
Affiliations:
-;-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Year:
2001

Citing 4
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Abstract

In this paper, a new method for edge detection in presence of impulsive noise based into the use of Support Vector Machines (SVM) is presented. This method shows how the SVM can detect edge in an efficient way. The noisy images are processed in two ways, first reducing the noise by using the SVM regression and then performing the classification using the SVM classification. The results presented show that this method is better than the classical ones when the images are affected by impulsive noise and, besides, it is well suited when the images are not noisy.