Segmentation for Image Indexing and Retrieval on Discrete Cosines Domain

Abstract

This paper used region growing segmentation technique to segment the Discrete Cosines (DC) image. The classic problem of content Based image retrieval (CBIR) is the lack of accuracy in matching between image query and image in the database. By using region growing technique on DC image,it reduced the number of image regions indexed. The proposed of recursive region growing is not new technique but its application on DC images to build  indexing keys is quite new and not yet presented by many  authors. The experimental results show that the proposed methods on segmented images present good precision which are higher than 0.60 on all classes. So, it could be concluded that region growing segmented based CBIR more efficient   compared to DC images in term of their precision 0.59 and 0.75, respectively. Moreover, DC based CBIR can save time and simplify algorithm compared to DCT images. The most significant finding from this work is instead of using 64 DCT coefficients this research only used 1/64 coefficients which is DC coefficient.