Highly accurate IR automatic object recognition system

Yi-Tong Zhou; Todd W. Gutschow

doi:10.1117/12.161425

20 October 1993 Highly accurate IR automatic object recognition system

Yi-Tong Zhou, Todd W. Gutschow

Proceedings Volume 1957, Architecture, Hardware, and Forward-Looking Infrared Issues in Automatic Target Recognition; (1993) https://doi.org/10.1117/12.161425
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

In this paper, we present a new ATR system for detecting and recognizing targets from a single IR image frame based on neural networks and Gabor functions. It uses Gabor functions to locate potential targets without prior knowledge about their type, size, and orientation. Neural networks are then used to remove false alarms and generate target identification based on information provided by Gabor functions. The new system combines Gabor functions and neural networks in a highly efficient way such that high recognition accuracy rates can be achieved under battlefield conditions. The new system has been successfully tested on hundreds of single frame IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations, and very high recognition accuracy rates have been achieved.

Citation Download Citation

Yi-Tong Zhou and Todd W. Gutschow "Highly accurate IR automatic object recognition system", Proc. SPIE 1957, Architecture, Hardware, and Forward-Looking Infrared Issues in Automatic Target Recognition, (20 October 1993); https://doi.org/10.1117/12.161425

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KEYWORDS

Neural networks

Target detection

Target recognition

Detection and tracking algorithms

Automatic target recognition

Infrared imaging

Feature extraction

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