An Effective and Fast Hybrid Framework for Color Image Retrieval

TLDR: This paper presents a novel, fast and effective hybrid framework for color image retrieval through combination of all the low level features, which gives higher retrieval accuracy than other such systems.

Abstract: This paper presents a novel, fast and effective hybrid framework for color image retrieval through combination of all the low level features, which gives higher retrieval accuracy than other such systems. The color moment (CMs), angular radial transform descriptor and edge histogram descriptor (EHD) features are exploited to capture color, shape and texture information respectively. A multistage framework is designed to imitate human perception so that in the first stage, images are retrieved based on their CMs and then the shape and texture descriptors are utilized to identify the closest matches in the second stage. The scheme employs division of images into non-overlapping regions for effective computation of CMs and EHD features. To demonstrate the efficacy of this framework, experiments are conducted on Wang’s, VisTex and OT-Scene databases. Inspite of its multistage design, the system is observed to be faster than other hybrid approaches.