Detecting Straight Line Segments Using a Triangular Neighborhood

A novel straight line segment detection method is proposed in this paper, based on the theory of mapping straight line segment neighborhoods between the image and the HT spaces and the geometrical analysis of the HT butterfly wings. This paper makes full use of the information in the butterfly wings to detect the segments, i.e. detecting segments by matching its butterfly wings. Due to the fact that the butterfly changes its shape and orientation according to the segment parameters, this paper deduces an approximation of the butterfly wings with triangles by moving and/or flipping the segments to the position that minimizes the approximating error. This movement alleviates the computation and precision loss introduced by the butterfly distortions, because straight side triangular regions can be used to obtain the parameters of segments. Compared to existing methods that detect segments using HT data, the proposed method utilizes more information around the butterfly center, and hence is more effective, especially when it is used to detect collinear segments. The experiments verify the performance of the proposed method.