DocumentCode :
2570639
Title :
Salient region extraction based on intensity mapping for image retrieval
Author :
Congyan, Lang ; Xu De ; Ning, Li ; Songhe, Feng
Author_Institution :
Inst. of Comput. Sci. & Eng., Beijing Jiaotong Univ., Beijing, China
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
2177
Lastpage :
2180
Abstract :
Salient region extraction provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. In this paper, we propose a robust approach to extracting the salient region based on bottom-up visual attention. The main contributions are twofold: 1) Instead of the feature parallel integration, the proposed saliencies are derived by serial processing between texture and color feature. 2) A constructive approach is proposed for rendering an image by a non-linear intensity mapping, which can efficiently eliminate high contrast noise regions in the image. And then the salient map can be robustly generated for a variety of nature images. Finally, the salient region extracted by our algorithm is used for image semantic retrieval. Experiments show that the proposed algorithm can characterize the human perception well and achieve satisfied retrieval performance.
Keywords :
feature extraction; image denoising; image retrieval; image texture; adaptive content delivery; constructive approach; feature parallel integration; high contrast noise region elimination; human perception; image retrieval intensity mapping; image semantic retrieval; nonlinear intensity mapping; salient region extraction; serial processing; Biology computing; Colored noise; Computational modeling; Content based retrieval; Data mining; Humans; Image coding; Image generation; Image retrieval; Noise robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5346244
Filename :
5346244
Link To Document :
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