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Proceedings Paper

Development of a novel image processing method: the LPED method
Author(s): Chialun John Hu
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Paper Abstract

Local polar-edge detection (LPED) is a novel image processing method the author used in several computerized image systems in the last 3 years. It uses a novel edge-detection approach to detect the boundary points of a group of temperature-selected objects embedded in a large IR image frame. Then it uses a 2-D clustering method to group all boundary points into N sub-groups with each sub-group representing one particular high-temperature object. It will then be followed by finding the center of mass point, or CMP, of each sub-group. From each sub- group, the program will immediately find 36 radial distances between the CMP and the boundary. A 36-dimension analog vector can then be constructed from these 36 radial distances. This 36D analog vector is the ID vector to identify the object that has this particular boundary. This ID vector is independent of the object location and independent of the object orientation. But it is a unique property from object to object. Therefore it can be used to track and target any particularly shaped object, especially when the object is moving and the focusing is not very sharp. All these image-processing steps are automatically carried out in a super-fast speed, once when the IR- image is loaded into the program. Because of the super-short time used to implement the novel algorithm, automatic tracking and automatic targeting can therefore be carried out in real-time.

Paper Details

Date Published: 23 April 2012
PDF: 10 pages
Proc. SPIE 8398, Optical Pattern Recognition XXIII, 83980Q (23 April 2012); doi: 10.1117/12.920022
Show Author Affiliations
Chialun John Hu, Southern Illinois Univ. Carbondale (United States)
SunnyFuture (United States)


Published in SPIE Proceedings Vol. 8398:
Optical Pattern Recognition XXIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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