基于改进图像阈值分割算法的纱线疵点检测

Yarn defect detection based on improved image threshold segmentation algorithm

针对纺织行业纱线疵点检测方法可靠性差、灵敏度低、检测速度低的问题,提出一种基于数字图像处理的纱线疵点判定方法。首先,搭建纱线图像采集系统,完成纱线图像采集;其次,针对纱线边缘信息难处理以及传统双边滤波对椒盐噪声处理效果差的问题,对双边滤波进行改进,改进后的双边滤波可有效保存纱线边缘信息;再者,针对传统阈值分割计算量大、最佳阈值难以寻找的问题,对传统阈值分割算法进行改进,改进的阈值分割算法在保证处理效果的同时提高了整体算法的处理速度;最后,采用亚像素对纱线边缘进行计算,提高了纱线疵点检测的精确度。实验结果验证了算法的有效性及可靠性,该算法在提高精确度的同时将检测速度提高了20%以上,对提高纱线质量检测的准确性具有重要意义。

Aiming at the problems of poor reliability,low sensitivity and low speed of yarn defect detection in the textile industry,a new yarn defect detection method based on digital image processing was proposed.A yarn image acquisition system is built to obtain yarn image.In view of the difficulty of yarn edge information processing and the poor effect of traditional bilateral filtering on pepper-and-salt noise processing,the bilateral filtering was worked on for improvement,and the improved bilateral filtering was shown to be effective for preserving the yarn edge data.Furthermore,aiming at the problem of large amount of calculation and difficulty in finding the optimal threshold,the optimal threshold calculation method of traditional threshold segmentation algorithm is improved.The improved threshold segmentation algorithm not only ensures the processing effect,but also improves the processing speed of the whole algorithm.Sub-pixel is used to calculate the yarn edge and improve the accuracy of yarn defect detection.The experimental results verified the effectiveness and reliability of the algorithm,and increased the detection speed by more than 20%while improving the accuracy,which is of great significance for improving the accuracy of yarn quality detection.