Two-dimensional object alignment based on the robust oriented Hausdorff similarity measure

• Published in: IEEE transactions on image processing Vol. 10; no. 3; pp. 475 - 483
• Main Authors: SIM, Dong-Gyu, PARK, Rae-Hong
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-03-2001; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Alignment; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Computer vision; Exact sciences and technology; Heat treatment; High definition video; Image edge detection; Image processing; Information, signal and communications theory; Noise robustness; Object detection; Object recognition; Orientation; Pattern recognition. Digital image processing. Computational geometry; Pixels; Pollution measurement; Signal processing; Similarity; Statistical distributions; Statistics; Telecommunications and information theory; Transforms; Two dimensional; Two dimensional displays; Hausdorff dimension; Similarity; Image processing; Hough transformation; Binary image; Aerial photography; Distance measurement; Experimental study; Displacive transformation; Adaptation
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/83.908541

This paper proposes an oriented Hausdorff similarity (OHS) measure for robust object alignment. The OHS measure is introduced by replacing the distance concept of conventional Hausdoff distance (HD) algorithms by the similarity concept of the Hough transform (HT). The proposed algorithm can be considered as the modified directed HT using the distance transform (DT). The orientation information at each pixel is also used to remove incorrect correspondences.