An Improved Algorithm of Image Retrieval Based on Combined BTC Color Moments and DT-CWT

DOI

10.2991/wartia-16.2016.54How to use a DOI?

Keywords

Image Retrieval, YIQ, BTC Color Moments, DT-CWT, Feature Fusion

Abstract

Feature extraction is the key technology in the process of image retrieval based on content. This paper puts forward an improved algorithm of image retrieval based on combined BTC color moments and DT-CWT. We firstly select the YIQ color space as the feature extracted space due to the strong correlation between each component of RGB color space. Combined with block coding thought, this paper encodes three component images in YIQ color space into a binary bitmap and calculates the BTC color moment to represent the image color feature.In order to overcome the shortcomings of traditional wavelet transform direction, we make use of DT-CWT to extract statistical characteristics of each sub-band as texture features. Finally, we carry out the weighted summation of similarity degree of the extracted color and texture features to constitute the basis of image retrieval.The experimental results show that the color and texture features extracted by the above-mentioned algorithm have more advantages in image retrieval, which has a higher average precision than the similar algorithms.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huajie Cai
AU  - Yaxin Zhao
AU  - Guangyi Xie
PY  - 2016/05
DA  - 2016/05
TI  - An Improved Algorithm of Image Retrieval Based on Combined BTC Color Moments and DT-CWT
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 282
EP  - 287
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.54
DO  - 10.2991/wartia-16.2016.54
ID  - Cai2016/05
ER  -