Trouble of moving freight car detection system (TFDS) has become an important system for train daily safety check system. Given the diversity and complexity of train faults

manual train fault detection remains the main method

which requires considerable manpower and includes unstable safety factors. Therefore

automatic train fault detection has become an urgent need of the TFDS system. Several soft-connected components exist in coupler buffer images

which lead to the difficulty of automatic correction between two images. We use dynamic time warping (DTW) to realize region division among several soft-connected components in the same image. Based on comparative analysis between the same regions in standard and origin images

we can determine the difference of each component and obtain the train fault detection result. Before region division

we preprocess the coupler buffer image to eliminate the image rotation and scale problem. We maintain the longitudinal image gray value to form a one-dimensional vector. In the one-dimensional space

we conduct vector matching based on the DTW method and realize region division in coupler buffer. We calculate the similarity of soft components between two images in different column inspection stations. During preprocessing

we can reduce the gray difference of the same parts in two images by histogram matching. With the coarse correction model

we can eliminate the rotation and size differences in the same parts in two images

which are ready for vertical gray value statistical calculation. In DTW matching

the vertical gray statistical value can reflect the distribution of soft connection parts. The matching method is suitable to separate different parts and achieve part matching. Given that several parts of a coupler buffer are softly connected

accurate matching of all parts is difficult to realize by the global correction model. In this study

we adopt the DTW region matching method based on the vertical gray

which can effectively separate different components. Therefore

we can correct each region and facilitate subsequent comparative analyses.