DocumentCode :
183101
Title :
An improved image retrieval method based on SIFT algorithm and saliency map
Author :
Jing Liu ; Fang Meng ; Fangcheng Mu ; Yichun Zhang
Author_Institution :
Inf. Eng. Sch., Commun. Univ. of China, Beijing, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
766
Lastpage :
770
Abstract :
Image retrieval methods based on the Scale Invariant Feature Transform (SIFT) algorithm have good performance except for the characteristics of time-consuming and high dimension feature vectors. This paper realizes an improved image retrieval method combining saliency maps with SIFT. The saliency map algorithm is used to define and detect the visually salient image regions which will be used in feature extraction and feature matching. The experimental results show that the improved method can not only reduce the retrieval time, but also rule out the interference in image matching caused by the feature points in background.
Keywords :
feature extraction; image matching; image retrieval; transforms; SIFT algorithm; feature extraction; feature matching; high dimension feature vectors; improved image retrieval method; saliency map; scale invariant feature transform algorithm; visually salient image regions; Algorithm design and analysis; Feature extraction; Image color analysis; Image retrieval; Libraries; Testing; Vectors; Image Retrieval; SIFT; Saliency Map;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
Type :
conf
DOI :
10.1109/FSKD.2014.6980933
Filename :
6980933
Link To Document :
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