Computational Intelligence and Security

Abstract

Hough Transform (HT) is a powerful tool to detect straight lines in noisy images since it is a voting method. However, there is no effective way to detect line segments and dominate points, which are more important in pattern recognition and image analysis. In this paper, we propose a simple way to detect lines segments and dominate points simultaneously in binary images based on HT using generalized labelling. The new framework firstly detects straight lines using HT and then labels each black point of the image by considering the discrete errors of HT. Finally, the connectivity among the points having the same labels is checked in order to reduce the effect of noises and detect line segments properly. The experimental results show that our new framework is an powerful and effective way to detect line segments and dominate points in noisy binary images.