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Application of information measure and support vector machine in image edge detection

WANG Pei1,ZHANG Yanning1,SHEN Jiazhen1,LIU Juncheng2,   

  1. 1. Department of Computer Science and Engineering,Northwestern Polytechnical University,Xi'an 710072,China;2. Institute of Material Science and Engineering,Shandong University of Technology,Zibo 255091,China
  • Received:2005-02-21 Revised:1900-01-01 Online:2006-06-24 Published:2006-06-24
  • Contact: WANG Pei1,

Abstract: A novel method for image edge detection is presented based on information measurement and Support Vector Machine, which is called ISEDM (Information measure and support vector machine edge detection method). At first, a vector is constructed to fully describe a edge point information measure, which includes neighborhood homogeneity information measure, orientation information measure, and gradient strengths. Secondly, SVM is applied to train and classify the set of feature vectors, so that the edge of the image is detected. The experimental results show that ISEDM can not only effectively reduce the noises of the image, but also can precisely detect the edgeposition, and keep the image edges' details well.

Key words: information measure, support vector machine , edge detection

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