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Color Image Retrieval Based on Full Range AutoRegressive Model with Low-Level Features

Authors

A. Annamalai Giri1 and K. Seetharaman2, 1Sri Kuvempu First Grade College, India and 2Annamalai University, India

Abstract

This paper proposes a novel method, based on Full Range Autoregressive (FRAR) model with Bayesian approach for color image retrieval. The color image is segmented into various regions according to its structure and nature. The segmented image is modeled to RGB color space. On each region, the model parameters are computed. The model parameters are formed as a feature vector of the image. The Hotlling T2 Statistic distance is applied to measure the distance between the query and target images. Moreover, the obtained results are compared to that of the existing methods, which reveals that the proposed method outperforms the existing methods.

Keywords

FRAR model, query image, target image, feature vector, spatial features.

Full Text  Volume 4, Number 9