基于反向P-M扩散分割的缝线断线检测

Stitch Breakage Detection Based on Inverse P-M Diffusion Segmentation

目的实现面粉袋缝线断线自动化检测。方法设计反向P–M扩散分割的缝线断线检测方法。首先采集缝线图像,并进行灰度开运算,以消除复杂背景及面粉袋两边端线的干扰。针对现场光照变化、反射不均、面粉噪声等环境因素对缝线提取的影响,对面粉袋表面与缝线的灰度特征、梯度特征进行分析,设计反向P–M扩散因子,先将图像进行反向P–M扩散,将扩散后的图像与开运算处理后的图像进行差分处理,从而抑制复杂背景纹理,增强缝线与面粉袋的区分度,将阈值分割出的缝线与面粉袋顶端缝边长度进行对比,判断缝线是否断线。结果实验结果表明,利用该算法进行缝线检测实验,断线检测准确率达到96%,每张缝线图片处理时间只需120 ms。结论基于反向P–M扩散分割的缝线断线检测方法是一种无接触缝线断线检测新方法,具有准确率高、速度快等优点,满足面粉生产企业断线自动化检测的要求。

The work aims to realize automatic detection of flour bag stitch breakage.A inverse P-M diffusion seg-mentation method was designed to detect stitch breakage.First,the stitch image was collected for gray-scale opening op-eration to eliminate the interference of complex background and the end lines on both sides of the flour bag.In view of the effects of environmental factors such as on-site illumination change,uneven reflection and flour noise on the extraction of stitches,the gray-scale features and gradient features of the surface of flour bags and stitches were analyzed,and the in-verse P-M diffusion factor was designed.First,the image was inverse P-M diffused,and the diffused image was differen-tiated from the image after opening operation,so as to suppress complex background texture and enhance the differentia-tion between stitches and flour bags.The stitch segmented by the threshold value was compared with the stitch at the top of the flour bag in terms of length to judge whether the stitch was broken.The experimental results showed that,when the algorithm was used for stitch detection experiment,the accuracy of stitch breakage detection was 96%and the processing time of each stitch image was only 120ms.The stitch breakage detection method based on inverse P-M diffusion segmen-tation is a new non-contact stitch breakage detection method,which has the advantages of high accuracy and fast speed,and meets the requirements of automatic detection of stitch breakage in flour production enterprises.