Hough Transform For Target Detection In Infrared Imagery

An algorithm is described for detecting and recognizing targets in infrared imagery in real-time. Suspicious areas are selected from a large frame by a very fast pre-processor which flags suspicious locations based upon local statistics in the frame. For finding the outlines of the target, the Sobel operator is used to extract edge gradients and orientations, which are then mapped into parameter space by the Hough transformation. Normalization and sharpening operations applied in the parameter space subsequently enhance straight boundaries associated with possible targets. A discriminant function for the recognition of the targets is formed based upon the assumption that the four boundaries of the target produce four sharp peaks in the parameter space. The above algorithm successfully detected targets in 25 subimages selected form a large frame.