摘要： 由于成像特点及环境干扰，用于工件缺陷检测的红外热像通常较为模糊。为此，将空间域与频域结合的模糊C均值(FCM)聚类算法用于红外热像中缺陷及正常表面的分割。运用多种图像处理方法对原始红外热像进行预处理，将得到的高频图像及其邻域平均图像使用经典FCM聚类算法进行像素灰度的聚类。实验结果表明，该方法的分割效果较好。
关键词:
红外热像,
缺陷检测,
模糊C均值聚类,
图像分割,
高通滤波,
直方图均衡化
Abstract: Imaging principle and environment disturbance have lowered the definition of the infrared thermal image. Aiming at this problem, an infrared thermal image processing framework is proposed based on Fuzzy C-means(FCM) clustering algorithm with spatial and frequency information. A sequence of preprocessing is applied to the original infrared thermal image. FCM with spatial and frequency information is used on the preprocessed image to segment defect and normal surface of a part. Experimental results show that the proposed infrared thermal image processing framework is very effective to detect the surface defect of a metal part.
Key words:
infrared thermal image,
defect detection,
Fuzzy C-means(FCM) clustering,
image segmentation,
highpass filtering,
histogram equalization
中图分类号:
谢静, 徐长航, 陈国明, 王玉. 空间域与频域结合的FCM红外热像分割方法[J]. 计算机工程, 2012, 38(15): 201-203,207.
XIE Jing, XU Chang-Hang, CHEN Guo-Meng, WANG Yu. Infrared Thermal Image Segmentation Method Using FCM Integrated with Spatial and Frequency Domain[J]. Computer Engineering, 2012, 38(15): 201-203,207.