文章基本信息

标题：Color Image Retrieval Based on Full Range AutoRegressive Model with Low-Level Features
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作者：A. Annamalai Giri ; K. Seetharaman
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2014
卷号：4
期号：9
页码：121-130
DOI：10.5121/csit.2014.4911
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This paper proposes a novel method, based on Full Range Autoregressive (FRAR) model withBayesian approach for color image retrieval. The color image is segmented into various regionsaccording to its structure and nature. The segmented image is modeled to RGB color space. Oneach region, the model parameters are computed. The model parameters are formed as afeature vector of the image. The Hotlling T2 Statistic distance is applied to measure the distancebetween the query and target images. Moreover, the obtained results are compared to that ofthe existing methods, which reveals that the proposed method outperforms the existing methods.
关键词：FRAR model; query image; target image; feature vector; spatial features.