Content-based image retrieval using computational visual attention model

2015 ◽  
Vol 48 (8) ◽  
pp. 2554-2566 ◽  
Author(s):  
Guang-Hai Liu ◽  
Jing-Yu Yang ◽  
ZuoYong Li
Array ◽  
2020 ◽  
Vol 7 ◽  
pp. 100027
Author(s):  
S. Sathiamoorthy ◽  
A. Saravanan ◽  
R. Ponnusamy

2011 ◽  
Vol 40 (7) ◽  
pp. 1025-1030
Author(s):  
黄传波 HUANG Chuanbo ◽  
金忠 JIN Zhong

2012 ◽  
Vol 30 ◽  
pp. 542-545 ◽  
Author(s):  
Satrajit Acharya ◽  
M.R.Vimala Devi

Author(s):  
Z. F. Shao ◽  
W. X. Zhou ◽  
Q. M. Cheng

Low-level features tend to achieve unsatisfactory retrieval results in remote sensing image retrieval community because of the existence of semantic gap. In order to improve retrieval precision, visual attention model is used to extract salient objects from image according to their saliency. Then color and texture features are extracted from salient objects and regarded as feature vectors for image retrieval. Experimental results demonstrate that our method improves retrieval results and obtains higher precision.


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