Abstract:
Rail edge detection is the key technology of tracking foreign matter intrusion detection. In view of the rail images are often affected by different degrees of noise in the acquisition process and the traditional edge detection methods are difficult to accurately detect the rail edge, an adaptive gray morphological method for rail edge detection based on MMSE (multi-scale and multi-direction structural elements) is proposed in this paper. Firstly, according to the noise characteristics of the track images, the morphological filtering algorithm of multi-scale structural elements are used to carry out the adaptive filtering operation on the track images, so as to enhance the rail edge and suppress the noise. Then the multi-direction adaptive gray morphological edge detection operator is used to detect the rail edge of the filtered track images. Experiments show that: This algorithm can not only effectively filter out the noise in the collected images, but also detect the rail edge in the track images accurately.