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Proceedings Paper

Gabor wavelet filters and fusion for distortion-invariant multiclass object detection
Author(s): David P. Casasent
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Paper Abstract

Several different new Gabor wavelet filters are described: the Gabor transform (GT) filter consists of real, imaginary, and clutter filters; the Gabor basis function (GBF) filter uses a Gabor basis function for each training image; the morphological wavelet transform (MWT) filter includes a Gabor transform clutter map filter that locates clutter regions of a scene. These filters ar all shift-invariant and distortion-invariant. They are employed for detection: location of the positions of all object regions of interest (ROIs) in an input scene. Fusion of multiple filter outputs is used to reduce false alarms. This paper emphasizes the role for Gabor wavelet filters in detection and for producing a clutter map. Major emphasis is given to the final version of the Gabor wavelet clutter map portion of our MWT algorithm (this is our best detection algorithm). New detection and fusion results with a consistent database and thresholds are provided.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205409
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 2491:
Wavelet Applications II
Harold H. Szu, Editor(s)

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