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Proceedings Paper

Morphological wavelet transform for distortion-invariant object detection in clutter
Author(s): Anqi Ye; David P. Casasent
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Paper Abstract

We developed an approach combining morphological processing and wavelet transforms to detect multiple objects in an input scene. The input scene contains different types of background clutter regions and multiple objects in different classes, with different object aspect views, different object representations, hot/cold/bimodal/partial object variations, and high/low object contrast variations. Our approach provides high detection rates and low false alarm rates. The most computationally demanding operations required are realizable on an optical correlator.

Paper Details

Date Published: 15 March 1994
PDF: 13 pages
Proc. SPIE 2242, Wavelet Applications, (15 March 1994); doi: 10.1117/12.170054
Show Author Affiliations
Anqi Ye, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 2242:
Wavelet Applications
Harold H. Szu, Editor(s)

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