Title :
A domain independent Genetic Programming approach to automatic feature extraction for image classification
Author :
Atkins, Daniel ; Neshatian, Kourosh ; Zhang, Mengjie
Author_Institution :
Sch. of Eng. & Comput. Sci., Victoria Univ. of Wellington, Wellington, New Zealand
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.
Keywords :
feature extraction; genetic algorithms; image classification; automatic image feature extraction; baseline system; classifier system; domain independent genetic programming; human-extracted features; image classification; Accuracy; Feature extraction; Filtering; Genetic programming; Humans; Object detection; Pixel;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949624