Steel rail surface damage detection method based on pulse coupling neural network
A technology of pulse-coupled neural and detection methods, applied in biological neural network models, neural architectures, image data processing, etc., can solve problems such as difficulty in comprehensive coverage, low degree of intelligence, limited and one-sided detection results, etc.
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[0076] The present invention will be further described below through specific embodiments in conjunction with the accompanying drawings. These embodiments are only used to illustrate the present invention, and are not intended to limit the protection scope of the present invention.
[0077] A rail surface damage detection method based on pulse-coupled neural network detects the position and size of rail surface defects and classifies them through the analysis and processing of image data, and finally points out the type of track defects, which includes the following four steps:
[0078] S1, image preprocessing;
[0079] S2, preliminary detection of defects based on pulse-coupled neural network;
[0080] S3, accurate calculation of features;
[0081] S4, defect classification.
[0082] In the step S1, in the data filtering process of extracting the track part in the image, the present invention adopts the horizontal projection method to extract the rail surface image, because...
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