Accurate and efficient curve detection in images: the importance sampling Hough transform

PATTERN RECOGNITION

卷:35

Article

Walsh, D ; Raftery, AE

关键词: clustering;    importance sampling;    Hough transform;    probabilistic Hough transform;    target distribution;   

DOI  :  10.1016/S0031-3203(01)00114-5

来源: Elsevier

【 摘 要 】

The Hough transform is a well known technique for detecting parametric curves in images. We place a particular group of Hough transforms, the probabilistic Hough transforms. in the framework of importance sampling. This framework suggests a way in which probabilistic Hough transforms can be improved: by specifying a target distribution and weighting the sampled parameters accordingly to make identification of curves easier. We investigate the use of clustering techniques to simultaneously identify multiple curves in the image. We also use probabilistic arguments to develop stopping conditions for the algorithm. Results from applying Our method and two popular versions of the Hough transform to both simulated and real data are shown. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

【 授权许可】

Free