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基于Gabor濾波器和HOG特征的織物疵點(diǎn)檢測
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華中科技大學(xué),華中科技大學(xué),華中科技大學(xué),華中科技大學(xué)

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Fabric defect detection based on Gabor filter and HOG feature
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Huazhong University of Science and Technology,Huazhong University of Science and Technology,Huazhong University of Science and Technology,Huazhong University of Science and Technology

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    摘要:

    針對織物疵點(diǎn)檢測問(wèn)題,提出了一種基于Gabor濾波器和方向梯度直方圖(HOG)特征的織物疵點(diǎn)檢測算法。首先使用3個(gè)尺度、4個(gè)方向的Gabor濾波器組對織物圖像進(jìn)行濾波,并做融合處理,增強織物圖像疵點(diǎn)區域和背景紋理之間的對比度;然后使用雙邊濾波減弱圖像背景紋理和噪聲的影響;最后將圖像劃分成均勻子塊,提取每個(gè)子圖像塊的HOG特征,利用圖像疵點(diǎn)區域和背景紋理的HOG特征差異進(jìn)行閾值分割實(shí)現織物疵點(diǎn)的檢測。實(shí)驗選取5種常見(jiàn)織物疵點(diǎn)進(jìn)行驗證,并與傳統的Gabor濾波算法進(jìn)行了實(shí)驗對比,結果表明該算法可以較好的抑制織物背景紋理的干擾,更加準確的檢測出織物疵點(diǎn)。

    Abstract:

    Aiming at the problem of detection of fabric defect, a fabric defect detection method based on Gabor filter and Histogram of Oriented Gradient(HOG) feature is presented. Firstly, a bank of Gabor filters with three scales and four directions are used to process the fabric image, through image fusion, the contrast between the defect zone and the background texture in the fabric image is enhanced; Then, the bilateral filter is used to weaken the influence of the background texture and noise of the fabric image; And Finally, the filtered image is divided into small image blocks with the same size, after extracting the HOG feature of each sub-image block, threshold segmentation is executed based on the difference of the HOG feature between defect area and background texture to realize the detection of fabric defect. Five normal fabric defects are tested, and a contrast experiment with the traditional Gabor algorithm is conducted. The experiment results show that the algorithm can better suppress the interference of the background texture and detect fabric defects more accurately.

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湯曉慶,黃開(kāi)興,秦元慶,周純杰.基于Gabor濾波器和HOG特征的織物疵點(diǎn)檢測計算機測量與控制[J].,2018,26(9):39-42.

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  • 收稿日期:2018-02-12
  • 最后修改日期:2018-03-26
  • 錄用日期:2018-03-26
  • 在線(xiàn)發(fā)布日期: 2018-09-14
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