关键词: 图像处理；路径识别；MATLAB；大津法；八邻域算法

Abstract: In order to solve the problems of insufficient perception image processing accuracy and poor anti-interference ability of path recognition in complex road environment, this paper designs a multi-stage optimization method that integrates the Otsu's method, the eight-neighborhood boundary tracking algorithm and the median filter, and verifies the effectiveness of the scheme by MATLAB simulation. The proposed method achieves systematic improvement through a three-level processing mechanism: the original Otsu's method with dynamic threshold adjustment is used to improve the image segmentation accuracy under complex lighting, the path contour features are extracted by the eight-domain boundary tracking algorithm, and the path topology optimization and noise suppression are realized by combining median filtering, so as to improve the anti-interference ability of the system as a whole. Experiments show that the proposed method reduces the standard deviation of path coordinates by about 50%, which not only improves the image processing accuracy, but also significantly strengthens the robustness of path recognition, thereby improving the tracking reliability of the intelligent car.

Key words: image processings; path recognition; MATLAB; Otsu's method; eight-neighborhood algorithm