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

Key words:  morphological algorithm  infrared image  defect detection  connected component  image segmentation

Abstract:

An infrared thermal image processing framework to detect surface defect of a steel specimen was proposed. It includes 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 l>ased 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 can obtain precise defect information of a steel specimen. It can be used as infrared detection and automatic identification means for components with surface defects.