Automatic image registration and target recognition with multi-resolution hybrid evolutionary algorithm

Igor V. Maslov

doi:10.1117/12.541895

9 August 2004 Automatic image registration and target recognition with multiresolution hybrid evolutionary algorithm

Igor V. Maslov

Proceedings Volume 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII; (2004) https://doi.org/10.1117/12.541895
Event: Defense and Security, 2004, Orlando, Florida, United States

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 M_R; 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.

Citation Download Citation

Igor V. Maslov "Automatic image registration and target recognition with multiresolution hybrid evolutionary algorithm", Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); https://doi.org/10.1117/12.541895

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