A new hough transform operated in a bounded cartesian coordinate parameter space
Gen Ke Yang, Junping Hu, Zhicheng Hou, Gong Zhang, Weijun Wang · IET Image Processing · 2022
Abstract In this paper, a new Hough transform is proposed to detect lines with geometric meanings. In the standard Hough transform, lines are parameterized by the length and orientation of the normal vector from the origin to the line. The parameter space of the standard Hough transform is presented in a polar coordinate system. Geometric measurements such as distance and angle are not suitable in polar coordinate space due to the inconsistency of the axes. To deal with this problem, a Hough transform which is carried out in a bounded Cartesian coordinate parameter space is developed. The lines are represented by their perpendicular feet with respect to a fixed point. Since the parameter space is in Cartesian coordinate space, it is intuitive to the researchers. When detecting the peaks in the parameter space, distance and angle constraints can be applied. The effectiveness of the proposed method has been illustrated by two applications, that is, lane line detection and convex polygon extraction. The results show that the proposed Cartesian coordinate Hough transform is suitable for detecting meaningful lines.