Multitarget and multibackground classification algorithm using neural networks

Rustom Mamlook; Wiley E. Thompson

doi:10.1117/12.154976

3 September 1993 Multitarget and multibackground classification algorithm using neural networks

Rustom Mamlook, Wiley E. Thompson

Proceedings Volume 1955, Signal Processing, Sensor Fusion, and Target Recognition II; (1993) https://doi.org/10.1117/12.154976
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

A multi-target and multi-background classification algorithm using neural networks is presented. The algorithm uses a feedforward neural network algorithm, a double window filter, and thresholds to classify an image into targets and backgrounds. This algorithm's performance differs from that of the K-nearest neighbor (K-NN) classifier algorithm in that (1) it provides noiseless classification, (2) it is faster, and (3) it provides better accuracy. Examples are given to illustrate the results.

Citation Download Citation

Rustom Mamlook and Wiley E. Thompson "Multitarget and multibackground classification algorithm using neural networks", Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); https://doi.org/10.1117/12.154976

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