Digital infrared thermography is suitable for monitoring the planar two-dimensional temperature distribution of curved surfaces of objects by sensing their infrared radiation. Cardiac infrared thermography also has a thermal coronary angiography alias. This study proposes a digital image processing methodology for locating blood clot blockage. This methodology contains four consequent processes. The two-dimensional gray scale infrared thermograph pixels are first binarized and classified as background or coronary arteries using multi-thresh adaptive segmentation. The coronary artery contours are extracted from segmented raw pixels using continuous pepper-like pixel removal, erosion, subtraction, recursive neighborhood visiting, contour point-list construction and short edge deletion. In the third process one coronary artery branch is selected by physicians for calculating the longest curved central axis using morphological thinning and neighborhood analysis. In the last process the nearest left and right distances from each pixel along the directional central axis to its corresponding boundary contour are added as the coronary artery variable diameter at the current pixel's position. A variable diameter versus straighten length diagram along this axial curved path is plotted to provide useful physiological information to the physician. An obstruction rate equation is then defined to calculate the possible vascular blockage positions with the local minimal rates. Finally, preoperative cases are tested to prove the predictive positions are correct in comparison to individual patient myocardial perfusion imaging.