DocumentCode :
545445
Title :
Improved SIFT features in image retrieval using
Author :
Zhao, Jie ; Xin, Tingfang ; Men, Guozun
Author_Institution :
Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
Volume :
2
fYear :
2011
fDate :
11-13 March 2011
Firstpage :
393
Lastpage :
397
Abstract :
In this paper, based on SIFT feature algorithm, the SIFT feature descriptor is improved, the area of feature points used to construct a new circular region feature descriptor, thus improving the characteristics of the problem of high dimension, but also enhanced features descriptor of their own anti-rotation, and then two images by calculating the feature vector Euclidean distance, the findings were compared in order to achieve image matching, in building the image database to find the minimum distance vector with which to achieve the target image retrieval. Experimental results show that the algorithm not only has the scale, translation, rotation invariance, but also the use of more stable and faster image retrieval.
Keywords :
image matching; image retrieval; SIFT feature descriptor; circular region feature descriptor; feature vector Euclidean distance; image database; image matching; image retrieval; minimum distance vector; rotation invariance; Algorithm design and analysis; Artificial neural networks; Computer vision; Feature extraction; Image matching; Image retrieval; Pixel; Euclidean distance; Image matching; Image retrieval; SIFT feature descriptor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Research and Development (ICCRD), 2011 3rd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-839-6
Type :
conf
DOI :
10.1109/ICCRD.2011.5764158
Filename :
5764158
Link To Document :
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