DocumentCode
691956
Title
Research on Image Matching Algorithm Based on Local Invariant Features
Author
Jiaqi Liu ; Qiang Wu ; Xuwen Li
Author_Institution
Coll. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
fYear
2013
fDate
16-18 Oct. 2013
Firstpage
113
Lastpage
116
Abstract
As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant feature points, starting from feature point detection and description point of view, making up the traditional feature point extraction defects of small number and types. Meantime, proposes an improved similarity measure method based on the previously proposed new feature point detection and description algorithm, it improves the matching accuracy and real-time performance. Finally, compares the experiment results of SURF, SIFT and the improved algorithm proposed in this paper, the experimental results shows that the feature points extracted by the improved algorithm has fully affine invariance, and improved the accuracy and speed of image matching algorithm efficiently.
Keywords
affine transforms; feature extraction; image matching; real-time systems; SIFT; SURF; affine invariance; affine invariant descriptor; affine invariant detector; description algorithm; description point of view; feature point detection; feature point extraction defect; image matching algorithm; image matching technique; image-guided technology; local invariant feature point; local invariant features; matching accuracy; real-time performance; similarity measure method; Accuracy; Algorithm design and analysis; Detectors; Feature extraction; Image matching; Signal processing algorithms; Transforms; affine invariance; image matching; local invariant feature;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/IIH-MSP.2013.37
Filename
6846593
Link To Document