A Domain Independent Genetic Programming Approach to Automatic Feature Extraction for Image Classification

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Reference

Daniel Atkins and Kourosh Neshatian and Mengjie Zhang: A Domain Independent Genetic Programming Approach to Automatic Feature Extraction for Image Classification. Proceedings of the 2011 IEEE Congress on Evolutionary Computation, pp. 238-245, IEEE Press, 5-8 June 2011.

DOI

http://dx.doi.org/10.1109/CEC.2011.5949624

Abstract

In this paper we explore the application of Genetic Programming (GP) to the problem of domain-independent image feature extraction and classification. We propose a new GP based image classification system that extracts image features autonomously, and compare its performance against a baseline GP-based classifier system that uses human-extracted features. We found that the proposed system has a similar performance to the baseline system, and that GP is capable of evolving a single program that can both extract useful features and use those features to classify an image.

Extended Abstract

Bibtex

Used References

P. Espejo, S. Ventura, and F. Herrera, A survey on the application of genetic programming to classification, Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 40, no. 2, pp. 121-144, 2010. http://dx.doi.org/10.1109/TSMCC.2009.2033566

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