An Algorithm of Edge Detection Based on FSVM

Ai Ping Cai

doi:10.4028/www.scientific.net/AMM.321-324.1046

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 321-324An Algorithm of Edge Detection Based on FSVM

An Algorithm of Edge Detection Based on FSVM

Abstract:

The support vector machine (SVM) has been shown to be an efficient approach for a variety of classification problems. It has also been widely used in target identification and tracking, motion analysis, image segmentation technology. Traditional detection methods mostly exist pseudo-edge and poor anti-noise capability. Under these circumstances, developing an efficient method is necessary. In this paper, we propose a new detection algorithm based on FSVM, the main idea is to train classified sample and give all training data a degree of membership, increase punishment to the wrong sub-sample. Then training and testing the FSVM classification model. Finally, extract edge of the image by using FSVM classification model. Experimental results show that the new algorithm can detect a clear image edge and have a good anti-noise nature.

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Periodical:

Applied Mechanics and Materials (Volumes 321-324)

Pages:

1046-1050

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.321-324.1046

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Online since:

June 2013

Authors:

Ai Ping Cai

Keywords:

Edge Detection, Fuzzy Support Vector Machine, Membership

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