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Rapid detection method for fabric defects based on machine vision

机译:基于机器视觉的织物疵点快速检测方法

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A new detection method for the non-destructive test of fabric defects based on machine vision is proposed in this study. In the proposed method, (a) the raw image is pre-processed by figuring the contrast and intensity to a proper level, (b) candidate regions are detected using the HSI color model and dynamic binarization, (c) the characteristic line of the target is obtained by the gray weighted centroid algorithm and (d) the quality of the product is judged by the number of valid pixel in the candidate region and the separation angle calculated from the characteristic line. Taking the detection of diaper as an example, an automatic detection system is built with an industrial camera. The position of diaper elastic waist and angle of the waist label, which are the two major parameters in the test of diaper quality, are examined based on the proposed method. Experimental results indicate that this method can be applied efficiently and effectively while resolving the problem of relative weak illumination and low contrast, bringing down noises caused by wrinkle and stain, and achieving a stable online inspection.
机译:提出了一种新的基于机器视觉的织物疵点无损检测方法。在提出的方法中,(a)通过将对比度和强度计算到适当的水平来预处理原始图像,(b)使用HSI颜色模型和动态二值化来检测候选区域,(c)图像的特征线目标是通过灰色加权质心算法获得的,并且(d)产品的质量由候选区域中有效像素的数量和从特征线计算出的分离角来判断。以检测尿布为例,用工业相机建立了自动检测系统。在此基础上,研究了尿布弹性腰围的位置和腰围标签的角度,这是尿布质量测试中的两个主要参数。实验结果表明,该方法能够有效有效地解决照明相对较弱,对比度低的问题,减少皱纹和污点引起的噪声,实现稳定的在线检测。

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