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Proceedings Paper

Detection filters using wavelets, Gabor, morphology, and fusion
Author(s): Anqi Ye; David P. Casasent
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Paper Abstract

We consider detection (location of all likely regions of interest (ROIs) in a scene where objects may be) for multiple classes of objects in 3D distortions with contrast differences and severe clutter present. Two different algorithms using Gabor basis function (GBF) filters and morphological wavelet transform (MWT) filtering are considered. New final algorithm parameters are noted. We detail: the morphological portion of the MWT algorithm, our new fusion method to combine the morphological and Gabor wavelet clutter map portions of the MWT algorithm, and the MWT threshold selection technique. Initial results using a new peak sorting scoring method and new fusion scores for multiple algorithms to reduce false alarms are noted.

Paper Details

Date Published: 28 March 1995
PDF: 10 pages
Proc. SPIE 2490, Optical Pattern Recognition VI, (28 March 1995); doi: 10.1117/12.205781
Show Author Affiliations
Anqi Ye, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 2490:
Optical Pattern Recognition VI
David P. Casasent; Tien-Hsin Chao, Editor(s)

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