纺织学报 ›› 2015, Vol. 36 ›› Issue (11): 45-50.

• 纺织工程 • 上一篇    下一篇

应用目标稀少特征的织物疵点图像分割

  

  • 收稿日期:2014-11-03 修回日期:2015-04-13 出版日期:2015-11-15 发布日期:2015-11-10

Image segment of fabric defect based on object rarity feature

  • Received:2014-11-03 Revised:2015-04-13 Online:2015-11-15 Published:2015-11-10

摘要:

应用自适应阈值分割方法进行织物疵点检测,其阈值选择一直是研究的难点问题,为此,中研究目标特征的基础上,提出了一种利用目标稀少特征确定最佳阈值的织物疵点分图像分割方法。首先,对采集织物图像进行滑动均值滤波,以抑制正常织物纹理信息对疵点检测的影响;然后,对织物图像进行预分割以确定最佳稀少度,在此基础上计算出最佳分割阈值;最后,利用最佳阈值进行织物疵点图像分割,并采用形态学滤波消除伪目标及噪声。结果表明,本文方法能够解决织物疵点分割中的最佳阈值确定问题,能够从织物纹理中有效分割出疵点信息。

Abstract:

Segmentation method based on adaptive threshold is one of the most common detection methods of fabric defects and threshold valve directly affects the detection effect. This paper presented a new segmentation method of fabric defects based object rarity feature. First of all, the acquisition images are pretreatment using sliding average filtering; secondly, the fabric images after pretreatment are several pre-segmentation, and calculate for each segmentation obtained interest region number of object; on this basis, the largest difference of object interest region number about adjacent pre-segmentation determines the optimal threshold of fabric image segmentation; then, defects of fabric image are segmented based on optimal threshold; finally, using morphological filtering, noise elimination and false object are eliminated. The test results show that, compared with the common segmentation method, the recommended method can segment out the defects information integrity.

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