| Abstract: | This article presents a tractable and empirically accurate algorithm realizing a midlevel visual process for pattern recognition. The algorithm takes advantage of hypotheses provided by a high‐level visual process, thereby, attempting to extract a region in an image based on these hypotheses. The main focus is to recognize quadrilateral as well as arbitrarily shaped objects from synthetic and real‐world images. The novel approach is based on a study of the Hough Transform and its generalized version. To show overall usefulness of the algorithm, an extensive series of experiments was performed. In particular, occlusion and multiple object‐instances were tested, indicating the effectiveness of this work's approach.© 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 13, 201–207;2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10056 |
