Automatic feature extraction and image classification using genetic programming

In this paper, we propose a multilayer domain-independent GP-based approach to feature extraction and image classification. We propose two different structures for the system and compare the results with a baseline approach in which domain-specific pre-extracted features are used for classification. In the baseline approach, human/domain expert intervention is required to perform the task of feature extraction. The proposed approach, however, extracts (evolves) features and generates classifiers all automatically in one loop. The experiments are conducted on four image data sets. The results show that the proposed approach can achieve better performance compared to the baseline while removing the human from the loop.