摘要
对织物表面疵点自动识别方法进行了探讨。将信息熵引入图像处理中,先通过最大熵快速迭代算法对织物疵点区域进行分割,把疵点图像分为背景和目标两部分;然后找出疵点区域的中心并求出疵点区域在纬向和经向上的方差;最后通过两者的比值与设定常数的比较,判断出疵点类型。仿真实验表明该方法对常见织物疵点的检测是有效的。
It studied the automatic identifying approach of the fabric surface defects. The information entropy was introduced into the image processing, it segmented the region of the fabric defect by using the fast iterative algorithm of the maximum entropy, divid- ed the image into two parts which were the background and the objectives, then the center of the faults region was found out and the variance of zonal and warp in the faults region was determined, finally by comparing the ratio of the two parts with the predetermined constants, the type of defects was determined. Simulation experiment showed that this method is effective to detect common fabric defects.
出处
《纺织科技进展》
CAS
2010年第2期64-65,69,共3页
Progress in Textile Science & Technology
关键词
织物疵点
信息熵
疵点自动识别
疵点检测
fabric defects
information entropy
defects automatic identification
defect detection
作者简介
作者简介：赵静（1985-），女，硕士研究生在读，研究方向为图像处理。
