Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
A New Approach for Line Recognition in Large-size Images Using Hough Transform
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Accurate and robust line segment extraction by analyzing distribution around peaks in Hough space
Computer Vision and Image Understanding
On-board selection of relevant images: an application to linear feature recognition
IEEE Transactions on Image Processing
A statistical image fusion scheme for multi focus applications
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
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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.