Fabric defect detection method
A detection method and fabric technology, applied in image data processing, instrument, character and pattern recognition, etc., can solve problems such as weak adaptability, insignificant detection effect, and difficulty in effectively describing complex and diverse fabric textures. Improve adaptability, effectively and accurately detect defects
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[0078] A fabric defect detection algorithm based on the combination of improved weighted median filter and K-means clustering, specifically implemented according to the following steps:
[0079] Step 1, scale the fabric defect image to be detected to 256×256 pixels, and convert it into a grayscale image;
[0080] Step 2, carry out improved weighted median filter processing to the yarn image obtained after step 1;
[0081] Step 2.1, when processing a pixel p in the image I, only consider pixels within a local window R(p) of radius r centered on p, for each pixel q∈R(p), the weighted median filter is based on the corresponding The affinity of pixels p and q in the feature map f compares it with the weight W pq are associated, as shown in formula (1):
[0082] W pq =g(f(p),f(q)) (1)
[0083] where: f(p) and f(q) are features at pixels p and q in f. g is a typical influence function between adjacent pixels, which can be Gaussian exp{-||f(p)-f(q)||} or other forms;
[0084] S...
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