An Image Matching Algorithm Based on SIFT and Improved LTP

Author

Yi-Ming Liu ; Li-Fang Chen ; Yuan Liu ; Hao-Tian Wu

Author_Institution

Sch. of Digital Medium, Jiangnan Univ., Wuxi, China

fYear

2013

fDate

14-15 Dec. 2013

Firstpage

432

Lastpage

436

Abstract

SIFT is one of the most robust and widely used image matching algorithms based on local features. But the key-points descriptor of SIFT algorithm have 128 dimensions. Aiming to the problem of its high dimension and complexity, a novel image matching algorithm is proposed. The descriptors of SIFT key-points are constructed by the rotation invariant LTP, city-block distance is also employed to reduce calculation of key-points matching. The experiment is achieved through different lighting, blur changes and rotation of images, the results show that this method can reduce the processing time and raise image matching efficiency.

Keywords

feature extraction; image matching; transforms; SIFT algorithm; blur changes; city-block distance; image matching algorithm; image rotation; key-points descriptor; key-points matching; lighting; local features; rotation invariant LTP; Accuracy; Algorithm design and analysis; Complexity theory; Educational institutions; Image matching; Lighting; Vectors; LTP; SIFT; city-block distance; image matching; key-points;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security (CIS), 2013 9th International Conference on

Conference_Location

Leshan

Print_ISBN

978-1-4799-2548-3

Type

conf

DOI

10.1109/CIS.2013.98

Filename

6746434