Local texton XOR patterns: A new feature descriptor for content-based image retrieval

Abstract

In this paper, a novel feature descriptor, local texton XOR patterns (LTxXORP) is proposed for content-based image retrieval. The proposed method collects the texton XOR pattern which gives the structure of the query image or database image. First, the RGB (red, green, blue) color image is converted into HSV (hue, saturation and value) color space. Second, the V color space is divided into overlapping subblocks of size 2 × 2 and textons are collected based on the shape of the textons. Then, exclusive OR (XOR) operation is performed on the texton image between the center pixel and its surrounding neighbors. Finally, the feature vector is constructed based on the LTxXORPs and HSV histograms. The performance of the proposed method is evaluated by testing on benchmark database, Corel-1K, Corel-5K and Corel-10K in terms of precision, recall, average retrieval precision (ARP) and average retrieval rate (ARR). The results after investigation show a significant improvement as compared to the state-of-the-art features for image retrieval.