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Proceedings Paper

Moving object tracking by using a novel real-time 2D local-polar-edge-detection method
Author(s): Chialun John Hu
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Paper Abstract

The LPED (local polar edge detection) method is a newly developed 2D image processing method that automatically utilizes the center-of-mass polar coordinate to represent, in a unique way by a 36-dimension analog vector, the boundary of each object embedded in a picture frame. This 36D vector is the object ID for the particular object it represents. This ID vector is independent of the position of the object and independent of the orientation of the object, but it is a characteristic property from object to object. The background noises are automatically filtered out if the background objects are much smaller and much more randomly distributed than the objects of interest. This concise ID vector will not only identify the object precisely in a large picture frame where multiple-shaped objects lie, it will also track the object automatically when the object moves and it will record the data of movement periodically. I.e., it can measure automatically the distance of movement, the angular change of object-orientation, and the new locations of the central of mass of the moving object between successive sampling time intervals. In other words, it can automatically predict the near future movement of the tracked object. The applications of this novel image processing technique, to name a few, may be (1) automatic satellite-tracking and targeting of ground moving vehicles, (2) robotic identification of surrounding environment by some shape selected scenic part in the environment (e.g., the cross-section of an underground tunnel) with self guidance for the robot to go along a desired path through the whole tunnel without hitting the tunnel wall. This paper describes the principle of LPED and some extensive experimental results, regarding the application (1) described above, by utilizing a real-time soft-ware program designed by the author.

Paper Details

Date Published: 26 April 2011
PDF: 11 pages
Proc. SPIE 8055, Optical Pattern Recognition XXII, 80550F (26 April 2011); doi: 10.1117/12.882745
Show Author Affiliations
Chialun John Hu, Southern Illinois Univ. Carbondale (United States)

Published in SPIE Proceedings Vol. 8055:
Optical Pattern Recognition XXII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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