基于形态学方法的工件表面缺陷红外热像检测技术

Infrared thermal images detecting surface defect of steel specimen based on morphological algorithm

提出一种基于形态学理论的红外热像分割方法,用于工件表面缺陷的自动检测。首先在含缺陷钢制试件红外热成像检测试验的基础上,对工件的红外热像进行灰度化、高斯高通滤波、对数变换和二值化等方法相结合的增强处理;然后采用形态学方法,基于缺陷的空间连续性和缺陷与噪声的尺寸差别,设定连通分量所含像素数的阈值,最终实现红外热像的有效分割。结果表明,新的红外热像处理方法可以实现缺陷位置和形状的精确检测,可作为含缺陷部件的红外检测和自动识别手段。

An infrared thermal image processing framework to detect surface defect of a steel specimen was proposed. It ineludes two steps： First, gray processing, Gaussian high pass filter, logarithmic transformation and thresholding were used on the original infrared thermal image in sequence for contrast enhancement; Second, based on the spatial continuity of defect and the size difference between noise and defect, a segmentation method based on morphological algorithm was applied. The threshold number of pixels contained in connected component was set and the effective segmentation of the infrared thermal image was realized. Experimental results show that the proposed framework has very promising segmentation performance and （：an obtain precise defect information of a steel specimen. It can be used as infrared detection and automatic identification means for components with surface defects.