Pulsed thermographic image has the disadvantages of low-contrast, fuzzy-edge, and non-uniformity of illumination for the defect detection, thus, a defect determination method which combines digital detail enhancement (DDE) technology with maximum entropy multi-threshold segmentation method was proposed for the improvement of pulsed thermographic image. Firstly, the contrast between defects and the background was improved significantly after the image was processed with digital detail enhancement algorithm optimized with adaptive contrast enhancement (ACE) algorithm, and reducing the influence of illuminative non-uniformity on defect recognition. Secondly, the target defects with maximum entropy multi-threshold segmentation method optimized with genetic algorithm, and the contours of each defect with eight neighborhood method to get the contour pixels in a certain sequence. Finally, based on the sequential contour pixels, the perimeter and the area of each defect could be estimated respectively with Euclidean distances formula and Green's theorem. The experimental result shows that this method is feasible to estimate defect size quantitatively, and digital detail enhancement technology could improve the defect detectability of pulsed thermographic system in a certain extent.