Segmentation of thermal images for non-destructive evaluation of bridge decks

The objective of the project presented in this paper is to automate the detection of subsurface defects in concrete bridge decks using infrared thermography. The algorithm developed for this purpose is based on the region growing approach, which segments the image and identifies the voids without human interference or prior knowledge of the conditions. The segmentation algorithm starts with the hottest pixels in the image as seed points, and then regions are grown around them based on a neighborhood selection criterion. The algorithm was tested on images collected from concrete bridge deck specimens containing various man-made defects and also on a defect-free control model. The experimental work successfully identified defects in concrete bridge decks up to 3 in. below surface using thermograph imaging.