A gradient BYY harmony learning algorithm on mixture of experts for curve detection

Authors:
Zhiwu Lu;Qiansheng Cheng;Jinwen Ma
Affiliations:
Department of Information Science, School of Mathematical Sciences, and LMAM, Peking University, Beijing, China;Department of Information Science, School of Mathematical Sciences, and LMAM, Peking University, Beijing, China;Department of Information Science, School of Mathematical Sciences, and LMAM, Peking University, Beijing, China
Venue:
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
Year:
2005

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Abstract

Curve detection is a basic problem in image processing and has been extensively studied in the literature. However, it remains a difficult problem. In this paper, we study this problem from the Bayesian Ying-Yang (BYY) learning theory via the harmony learning principle on a BYY system with the mixture of experts (ME). A gradient BYY harmony learning algorithm is proposed to detect curves (straight lines or circles) from a binary image. It is demonstrated by the simulation and image experiments that this gradient algorithm can not only detect curves against noise, but also automatically determine the number of straight lines or circles during parameter learning.