Contrast, size, and orientation-invariant target detection in infrared imagery

Yi-Tong Zhou; Richard D. Crawshaw

doi:10.1117/12.44903

1 August 1991 Contrast, size, and orientation-invariant target detection in infrared imagery

Yi-Tong Zhou, Richard D. Crawshaw

Proceedings Volume 1471, Automatic Object Recognition; (1991) https://doi.org/10.1117/12.44903
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

Citation Download Citation

Yi-Tong Zhou and Richard D. Crawshaw "Contrast, size, and orientation-invariant target detection in infrared imagery", Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); https://doi.org/10.1117/12.44903

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