DocumentCode
550513
Title
Improved SURF algorithm based on SVM classification
Author
Chang Junlin ; Wei, Wei ; Liang Junyan
Author_Institution
China Univ. of Minning & Technol., Xuzhou, China
fYear
2011
fDate
22-24 July 2011
Firstpage
3083
Lastpage
3087
Abstract
An new SURF algorithm based on support vector machine is presented in order to solve the problem of mismatch between feature points. Put the data of the normalized Euclidean distance of feature points into support vector machine to achieve adaptive match after training SVM by data. The experiment by OpenCV library verify that the improved SURF algorithm proposed in this paper has higher accuracy than the old one. Besides, there is no significant increase in complexity.
Keywords
image classification; image matching; statistical analysis; support vector machines; Euclidean distance; OpenCV library; SURF algorithm; SVM classification; support vector machine; Classification algorithms; Computer languages; Computer vision; Euclidean distance; Feature extraction; Image matching; Support vector machines; Image Matching; OpenCV; SURF; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2011 30th Chinese
Conference_Location
Yantai
ISSN
1934-1768
Print_ISBN
978-1-4577-0677-6
Electronic_ISBN
1934-1768
Type
conf
Filename
6000852
Link To Document