Feature Selection and Reduction for Batik Image Retrieval

Abstract

Batik is the fabric which is truly unique to Indonesia. Batik image retrieval is the research area which focuses on image processing and image retrieving based on its characteristics. This study investigated the performance of the feature selection and reduction on the batik retrieval process. The feature employed in this experiment is the combination of four feature extraction methods, which are Gabor filter, log-Gabor filter, GLCM, and LBP. SFFS methods is used to carry out the selection of features, meanwhile, PCA is used to perform the reduction feature. Based on the experiment, PCA can increase the precision about 17%. Meanwhile, SFFS can improve the execution time 1800 times faster.