Recognition of Nonrigid Objects Using the Generalized Hough Transform

Important visual cues in images are edges and line contours. The application of feature detection algorithms does not necessarily provide a complete segmentation into closed contours. A medium level step to combine characteristic local primitives to global structures is required. The Hough Transform is well known as a robust transform which converts the global pattern detection problem into a local problem: finding evident maxima in parameter space, which is equivalent to detecting global structures in image space. It is a model-based approach which assumes that the contours to be detected are a priori represented by an exact model curve. However, objects in images are often slightly deformed, which impedes their successful recognition using the usual Hough techniques.