Stereo Matching and Image Inpainting Based on Binocular Camera

Abstract

Stereo matching is one of the key technologies in the field of computer vision. The depth map obtained by stereo matching contains the three-dimensional information of the scene. The use of depth map is of great significance in the three-dimensional reconstruction of the map and the autonomous navigation of the robot. Aiming at the accuracy and speed of stereo matching, this paper applies a semi-global stereo matching method to match corrected left and right perspective images. Because there are noise points and holes in the matched disparity map, which affect the image quality, a sample block filling method which combines mean filtering and point-by-point scanning is proposed to repair the image. Then a gradient priority selection mechanism is proposed to maintain the edge structure of the object in the process of restoration. Experimental results show that the proposed method is good for the restoration of holes and noises in disparity maps, and the processing speed is improved by about 30% compared with the traditional Criminisi algorithm.