Fast segmentation method for brake beam of freight train under complex background

In order to segment the brake beam of freight train accurately, a segmentation method comprising gray projection, discrete wavelet transform and adaptive segmentation is proposed to realize automatic failure recognition for trouble of moving freight car detection system (TFDS). The objects are segmented based on the correlation between distribution of gray scales and their location. The vertical gray projection is calculated, and the projection curve is analyzed using discrete wavelet transform. The extreme points which represent the edges of break beams are extracted, and the centerline can be fitted accordingly. Considering priori information in the image, a rectangular area in the plane is rotated and gray projection along the long axis is calculated within the area. An adaptive threshold is set based on the maximum and minimum of projection curve, and the characteristic peak can be selected. Then, the inclined brake beams are segmented. Experimental results indicate that 99 percent of the images can be correctly segmented, and average time cost of an image is 21.7 ms. The proposed method can correctly segment break beams in all-weather conditions, even when the original images have poor quality, which advances the engineering application for TFDS.