IR/Lidar automatic object recognition system

Yi-Tong Zhou; Demetrios Sapounas

doi:10.1117/12.277096

23 June 1997 IR/ladar automatic object recognition system

Yi-Tong Zhou, Demetrios Sapounas

Proceedings Volume 3069, Automatic Target Recognition VII; (1997) https://doi.org/10.1117/12.277096
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

A biologically inspired neural network (BINN) system for IR/LADAR object recognition is presented in this paper. The BINN system uses a local spatial frequency-based method to locate potential targets in a scene image. The potential targets are separated from background using a modified CORT-X boundary segmentation method and target classification is carried out by a multilayer perceptron based on the local spatial frequency features extracted from both IR and LADAR images. Because of the local spatial frequency features, CORT- X boundary segmentation method, and rich training sets used, the BINN system is insensitive to target background, brightness, contrast level, contrast reversal, and geometry relative to the sensor. The BINN system has been successfully tested on hundreds of pairs of real IR/LADAR images that contain multiple examples of military vehicles with different size and brightness/range in various background scenes and orientations.

Citation Download Citation

Yi-Tong Zhou and Demetrios Sapounas "IR/ladar automatic object recognition system", Proc. SPIE 3069, Automatic Target Recognition VII, (23 June 1997); https://doi.org/10.1117/12.277096

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