Extracting Image Features for Classification By Two-Tier Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Al-Sahaf:2012:CEC,

• title = "Extracting Image Features for Classification By Two-Tier Genetic Programming",
• author = "Harith Al-Sahaf and Andy Song and Kourosh Neshatian and Mengjie Zhang",
• pages = "1630--1637",
• booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary Computation",
• year = "2012",
• editor = "Xiaodong Li",
• month = "10-15 " # jun,
• DOI = "doi:10.1109/CEC.2012.6256412",
• address = "Brisbane, Australia",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Evolutionary Computer Vision",
• abstract = "Image classification is a complex but important task especially in the areas of machine vision and image analysis such as remote sensing and face recognition. One of the challenges in image classification is finding an optimal set of features for a particular task because the choice of features has direct impact on the classification performance. However the goodness of a feature is highly problem dependent and often domain knowledge is required. To address these issues we introduce a Genetic Programming (GP) based image classification method, Two-Tier GP, which directly operates on raw pixels rather than features. The first tier in a classifier is for automatically defining features based on raw image input, while the second tier makes decision. Compared to conventional feature based image classification methods, Two-Tier GP achieved better accuracies on a range of different tasks. Furthermore by using the features defined by the first tier of these Two-Tier GP classifiers, conventional classification methods obtained higher accuracies than classifying on manually designed features. Analysis on evolved Two-Tier image classifiers shows that there are genuine features captured in the programs and the mechanism of achieving high accuracy can be revealed. The Two-Tier GP method has clear advantages in image classification, such as high accuracy, good interpretability and the removal of explicit feature extraction process.",
• notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the EPS and the IET.",

}

Genetic Programming entries for Harith Al-Sahaf Andy Song Kourosh Neshatian Mengjie Zhang

Citations