Solving Line-feature Stereo Matching with Genetic Algorithms in Hough Space

This paper presents a method that converts the line-matching problem in image space into a simple point-matching problem in Hough space. By means of solving this point-matching problem, the correspondence between lines is derived. In this study, line features are first extracted in image space, and transformed into Hough space as points. Then, a point-feature based stereo matching problem is formulated and further constructed as an energy function for minimization. We propose a hybrid heuristic procedure, which includes the Hough transformation, point feature segmentation, Vector Quantization, and a genetic algorithm, to derive the minimal solutions of the energy function. Two experiments were conducted to verify the proposed method. Experimental results show that the proposed method effectively and efficiently solves the correspondence problem in Hough space.