Unsupervised detection of straight lines through possibilistic clustering

The unsupervised detection of an unknown number of straight lines in digital imagery is addressed. Based on possibilistic clustering an algorithm is proposed which does not require any assumption about the number of straight lines present in the edge map. Three major modifications are introduced with respect to existing clustering-based algorithms: the use of possibilistic clustering; a more sophisticated analysis of the clusters, including the possibility of rejecting non linear clusters; a bottom up strategy to evaluate how many straight lines the image contains. The effectiveness of the proposed scheme is proved by validating it against real world imagery