Coevolving feature extraction agents for target recognition in SAR images

Bir Bhanu; Krzysztof Krawiec

doi:10.1117/12.487539

12 September 2003 Coevolving feature extraction agents for target recognition in SAR images

Bir Bhanu, Krzysztof Krawiec

Proceedings Volume 5095, Algorithms for Synthetic Aperture Radar Imagery X; (2003) https://doi.org/10.1117/12.487539
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

This paper describes a novel evolutionary method for automatic induction of target recognition procedures from examples. The learning process starts with training data containing SAR images with labeled targets and consists in coevolving the population of feature extraction agents that cooperate to build an appropriate representation of the input image. Features extracted by a team of cooperating agents are used to induce a machine learning classifier that is responsible for making the final decision of recognizing a target in a SAR image. Each agent (individual) contains feature extraction procedure encoded according to the principles of linear genetic programming (LGP). Like 'plain' genetic programming, in LGP an agent's genome encodes a program that is executed and tested on the set of training images during the fitness calculation. The program is a sequence of calls to the library of parameterized operations, including, but not limited to, global and local image processing operations, elementary feature extraction, and logic and arithmetic operations. Particular calls operate on working variables that enable the program to store intermediate results, and therefore design complex features. This paper contains detailed description of the learning and recognition methodology outlined here. In experimental part, we report and analyze the results obtained when testing the proposed approach for SAR target recognition using MSTAR database.

Citation Download Citation

Bir Bhanu and Krzysztof Krawiec "Coevolving feature extraction agents for target recognition in SAR images", Proc. SPIE 5095, Algorithms for Synthetic Aperture Radar Imagery X, (12 September 2003); https://doi.org/10.1117/12.487539

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KEYWORDS

Feature extraction

Image processing

Synthetic aperture radar

Visualization

Target recognition

Computer programming

Genetics

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