期刊
JOURNAL OF REAL-TIME IMAGE PROCESSING
卷 13, 期 3, 页码 431-447出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11554-015-0536-0
关键词
Attributed relational graph; Image representation; Content-based image retrieval; Saliency map; Real-time retrieval
类别
资金
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2013R1A1A20 12904]
The exponential growth in the volume of digital image databases is making it increasingly difficult to retrieve relevant information from them. Efficient retrieval systems require distinctive features extracted from visually rich contents, represented semantically in a human perception-oriented manner. This paper presents an efficient framework to model image contents as an undirected attributed relational graph, exploiting color, texture, layout, and saliency information. The proposed method encodes salient features into this rich representative model without requiring any segmentation or clustering procedures, reducing the computational complexity. In addition, an efficient graph-matching procedure implemented on specialized hardware makes it more suitable for real-time retrieval applications. The proposed framework has been tested on three publicly available datasets, and the results prove its superiority in terms of both effectiveness and efficiency in comparison with other state-of-the-art schemes.
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