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Image Search Using Similarity Measures Based on Circular Sectors

Authors

Jan Masek, Radim Burget, Lukas Povoda and Martin Harvanek, Brno University of Technology, Czech Republic

Abstract

With growing number of stored image data, image search and image similarity problem become more and more important. The answer can be solved by Content-Based Image Retrieval systems. This paper deals with an image search using similarity measures based on circular sectors method. The method is inspired by human eye functionality. The main contribution of the paper is a modified method that increases accuracy for about 8% in comparison with original approach. Here proposed method has used HSB colour model and median function for feature extraction. The original approach uses RGB colour model with mean function. Implemented method was validated on 10 image categories where overall average precision was 67%.

Keywords

CBIR, circular sectors, cross-validation, image features, image processing, image similarity, optimization

Full Text  Volume 5, Number 15