A Regularized Minimum Cross-entropy Algorithm on Mixture of Experts for Curve Detection

Curve detection is a basic problem in image processing and remains a difficult problem. In this paper, with the help of regularization theory, we aim to solve this problem via a gradient regularized minimum cross-entropy(RMCE) algorithm on the mixture of experts (ME) model, which can automatically make model selection. It is demonstrated by the simulation and image experiments that this gradient algorithm can not only detect curves (straight lines or circles) against noise, but also automatically determine the number of curves during parameter learning.