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Proceedings Paper

Automatic detection of targets using hierarchical spatial/temporal processing
Author(s): Eliezer Haber; Yehuda Sylman
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Paper Abstract

An algorithm for automatic target detection has been developed.An image is processed using a pyramidal structure in a two stage process. Each frame is spatially filtered to identify potential target areas. The temporal behavior of blobs identified is analyzed; targets are declared where blobs exhibit motion consistent with targets of interest. Targets of different sizes are detected at different pyramid levels. A single target will usually be detected at several levels. Integration of information from the various levels is essential. Two data merging approaches were examined. The first projects blobs from each level to the pyramid base. Blobs exhibiting target-like behavior are extracted. The second innovative approach builds tracks on each level. Only blobs jointed to tracks are projected to the base. Tracks are formed on these projections. Targets are declared on tracks that achieve a given quality. This hierarchical approach permits the system to operate with great sensitivity. False detections are eliminated at two stages. Most spurious blobs will not form tracks at the pyramid levels and will not be projected to the base. Tracking at the base eliminates others. Experimental results demonstrate high detection probability and low false alarm rate under a wide variety of conditions.

Paper Details

Date Published: 22 September 1997
PDF: 9 pages
Proc. SPIE 3110, 10th Meeting on Optical Engineering in Israel, (22 September 1997); doi: 10.1117/12.281401
Show Author Affiliations
Eliezer Haber, ElOp Electrooptics Industries Ltd. (Israel)
Yehuda Sylman, ElOp Electrooptics Industries Ltd. (Israel)

Published in SPIE Proceedings Vol. 3110:
10th Meeting on Optical Engineering in Israel
Itzhak Shladov; Stanley R. Rotman, Editor(s)

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