Auto-extracting Sub-pixel Line Feature of Digital Images Based on Hypothesis Testing
Fangfang Li · Acta Geodaetica et Cartographica Sinica · 2013
Line feature,which has abundant semantic information,is a very important intermediate level symbol in digital image processing and pattern recognition.In order to resolve many issues in current line extraction algorithms,a robust and sub-pixel approach for extracting straight lines is presented.When fractured short line segments need to be combined into groups,which is called as perceptual organization,an algorithm based on hypothesis testing and fuzzy fusion is put forward.This algorithm combines fractured line segments into a whole one according to geometric topology,physics spectral information,global and local scale information.Then,the least square template matching algorithm(LSTM) is implemented to get the higher precise line segments.The experimental results show that the proposed algorithm is more efficient,which can get richer and sub-pixel straight lines from aerial and ground images.