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Proceedings Paper

Multi-Sensor Processing: Object Detection And Identification
Author(s): Suzanne Liebowitz; David Casasent
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Paper Abstract

Following a brief review of multi-sensor image processing techniques for obstacle detection, we consider a new method to employ range data to extract object regions of interest from an outdoor natural scene. Our emphasis and intent is scene analysis and object identification in the face of 3-D distortions using range sensor data. The range image is segmented into background/nonbackground pixels based on line-by-line processing. Non-background pixels are clustered together by a projection-based technique to determine possible regions of interest. Following extraction of object regions of interest, we can merge the range and other sensor image data to obtain multi-sensor images of the regions in the field of view. Emphasis in this paper is given to the aforementioned tasks; however, for completeness, the remainder of the full processor is briefly described. The use of a hybrid optical/digital processor for such tasks is noted.

Paper Details

Date Published: 1 January 1987
PDF: 18 pages
Proc. SPIE 0852, Mobile Robots II, (1 January 1987); doi: 10.1117/12.968236
Show Author Affiliations
Suzanne Liebowitz, Carnegie Mellon University (United States)
David Casasent, Carnegie Mellon University (United States)

Published in SPIE Proceedings Vol. 0852:
Mobile Robots II
Wendell H. Chun; William J. Wolfe, Editor(s)

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