Rail Surface Defect Detection Based on Textural Features
In order to improve the accuracy of rail surface defect identification,the method of bilateral filtering is used to remove noise and preserve the defect boundary.The threshold calculation method is optimized,combined with the number of gray histogram peaks,adopts the corresponding threshold calculation method to ensure that the binarization results are reliable and effective.Frequency domain filter optimization is applied to eliminate low fre-quency and subtle interference areas.Through the invariant moment feature extraction,the falling block and col-lapse defects can be distinguished effectively,which improves the intelligence level and accuracy of rail surface defect identification.
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