A rail foreign matter detection method based on low-rank matrix factorization
A low-rank matrix, foreign object detection technology, applied in the field of computer vision, can solve problems such as train safety hazards, throwing out of the window, etc., and achieve good robustness.
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[0041] In this embodiment, a representative rail foreign object image taken based on a space-based platform is taken as an example, such as figure 2 shown. Line detection is performed on the source image, and the result is as follows image 3 As shown in , and filter the calculated straight line to extract the railway track area of interest.
[0042]Extract the pixel vector of the region of interest and perform clustering processing, divide it into two subsets of sleepers and stones, and perform low-rank matrix decomposition on the matrix formed by the two subsets to obtain the low-rank matrix D, and make the difference between the original matrix and the low-rank matrix to obtain The foreground matrix E and the foreground matrix are filtered and thresholded to determine the position of the foreign object and marked in the source image. The experimental results are as follows Figure 4 shown.
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