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Proceedings Paper

Automatic image registration and target recognition with multi-resolution hybrid evolutionary algorithm
Author(s): Igor V. Maslov
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Paper Abstract

A novel method for multi-resolution automatic target recognition is described that employs the hybrid evolutionary algorithm and image transform in a form of image local response. The recognition task is re-formulated as a nonlinear global optimization problem, i.e. the search for a proper transformation A(V) that provides the best match between the images of the target and the scene. Given the images of the scene and the targeted object located in the scene, the proposed method repeatedly applies response analysis on different resolution levels (zooming in), in order to find the region of interest (ROI) containing the target in the large-scale image of the scene. On every resolution level, the response matrices are computed for the images of ROI and the target. Cross correlation of the response matrices built for ROI and the target outlines the potential locations of the latter. Once the locations are successfully identified, the algorithm zooms in on the found locations. The hybrid evolutionary algorithm is applied to the response matrices MR; it attempts to minimize the least squared difference of the pixel values of the response matrices corresponding to the images, thus searching for the correct parameter vector V for the targeted object with the reference to ROI.

Paper Details

Date Published: 9 August 2004
PDF: 8 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.541895
Show Author Affiliations
Igor V. Maslov, CUNY/Graduate Ctr. (United States)

Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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