Vanishing point detection method in complex environment of mine roadway

By detecting and identifying the vanishing point position in the image, it is able to assist mobile robots in mines roadways for autonomous navigation. The existing vanishing point detection methods have large errors in the mine roadway with poor lighting conditions and insufficient structured information. In order to solve the above problems, a vanishing point detection method in complex environment of mine roadways is proposed. Firstly, the image is pre-processed by reducing, filtering, graying, etc. This method can reduce the calculation amount significantly and the straight line characteristics can be better preserved. Then, the straight line detection algorithm is used to detect the straight line of the image. The straight line length threshold and the average gradient constraint are introduced to eliminate the interference line with small length and the interference line generated by shadows in the image respectively. Moreover, the block matching algorithm is used to generate the block motion trajectory straight line of the image. Finally, the straight lines after removing the interference and the block motion trajectory straight lines are converted into sample points in the parameter space. The outlier factor value of each sample point is calculated by the local anomaly factor algorithm, and the outlier factor value of the sample point and the length of the corresponding straight line are used as the criteria to measure the importance of the sample points. On this basis, the weight function of the weighted regression algorithm is designed to obtain the best estimate of the vanishing point. The experimental results on the mine roadway data set and public data set show that compared with the edge-based vanishing point detection method and the deep learning-based vanishing point detection method, the method in this paper has stronger robustness to light changes. It has higher accuracy in complex environment with poor lighting conditions and lack of straight line information, and has better real-time performance than the vanishing point detection method based on deep learning. This method can better meet the needs of mine roadway robot navigation.