TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Region Division for Large-scale Image Retrieval |
| 영문제목(English Title) |
Region Division for Large-scale Image Retrieval |
| 저자(Author) |
Yunbo Rao
Wei Liu
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| 원문수록처(Citation) |
VOL 13 NO. 10 PP. 5197 ~ 5218 (2019. 10) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.
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| 키워드(Keyword) |
Image retrieval
image color analysis
image texture
image similarity measurement
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| 파일첨부 |
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