运用机器视觉技术解决织物探边问题是当今织物探边领域的主要方法,探边算法是定型机中提高织物探边速度与精度的关键。针对实际生产中对探边系统的要求,研究了多种图像处理算法应用于织物探边时存在的问题,通过分析采集到的具有多种特征的织物灰度图像,提出了一种自适应阈值探边算法。该算法可以快速、准确地得到不同织物的边缘位置。实验证明,该算法的探边精度可达0.1 mm,算法运算规模小,满足探边算法对高速度与高精度的要求,为后续探边系统的整体设计提供了支持。

Using machine vision technology to solve the problem of textile edge detection is the primary method in the field of textile edge detection. Edge detection algorithms are the key to improve the speed and precision of textile edge detection. In this paper, according to the requirements of the edge detection system in practical production, the problems existing in various image processing algorithms applied to the textile edge detection are studied, and the grayscale images of the textile with various characteristics are analyzed. Then an adaptive threshold edge detection algorithm is proposed. The algorithm can obtain the edge position of different textile quickly and accurately. The experiments show that the accuracy of the algorithm can reach 0.1 mm and the algorithm has a small running scale, which meets the requirements of high speed and high precision for the edge detection algorithm, and provides support for the following overall design of the edge detection system.