Fabric defect detection method and system based on over-complete convolutional neural network
A convolutional neural network and defect detection technology, applied in the field of fabric surface defect detection, can solve the problems of reduced resolution, the model cannot well identify small defects or refine the boundaries of defects, etc., to facilitate extraction and improve refinement. Effect
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[0043] The following will be combined with the accompanying drawings in the embodiments of the present invention, the technical solution in the embodiments of the present invention will be described clearly and completely, it is clear that the embodiments described are only a part of the embodiment of the present invention, not all embodiments. Based on embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative work, are within the scope of protection of the present invention.
[0044] Reference Figure 1 As shown, the present invention discloses a fabric defect detection method based on an overly complete convolutional neural network, comprising the following steps:
[0045] S101: Image acquisition steps: using image acquisition equipment, collect fabric images;
[0046] S102: Image preprocessing step: pre-processing the fabric image to obtain the pre-treated fabric image;
[0047] S103: Detection step: Input...
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