An Image Retrieval Method Using Homogeneous Region and Relevance Feedback

Abstract

Relevance feedback and region based image retrieval are two effective ways to improve accuracy in content-based image retrieval. In this paper, we propose a content-based image retrieval method using relevance feedback and homogeneous region. By extracting a number of homogeneous color regions from the image and calculating the occurrence frequency of regions, we convert image feature vectors to weighted vectors. On the basis of the weighted vectors, we calculate the similarity between two weighted vectors and using relevant feedback technique. Our experimental results on a Wang database of over 10,000 images suggest that the technique results in which is close to user's intention better than the CBsIR and CCH methods.  Index Terms-content based image retrieval, weighted vectors, feature vectors, machine learning.

An efficient semantic – Related image retrieval method

“…OrtegaBinderberger et al, 2004;D. Liu et al, 2009, Mattia Broilo et al, 2010Andre B et al, 2012;Hieu. V. V., Quynh.…”

“…As shown in Figure 1(a), the initial research which use this approach can found in [Smith, J.R et al, 1996;Ishikawa, Y et al, 1998;Porkaew, K. et al, 1999;D. Liu et al, 2009;Andre B et al, 2012;Hieu. V. V., Quynh N. H., 2014] represents a new query by a single point and adjusts the weights of feature components to find an optimal query point and distance function.…”