BROWSE
Detail
Conference Paper
F-SIFT and B-RANSAC - New Image Matching Algorithms
Cited - time in 
Share 
Share
- Authors
- Jae Kwang Lee, Chang-Joon Park, In-Ho Lee
- Issue Date
- 2007-01
- Citation
- Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV) 2007, pp.268-274
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper addresses two image matching algorithms based on SIFT and RANSAC. The proposed algorithms are F-SIFT (Frequency Scale Invariant Feature Transform) and B-RANSAC (Block Random Sample Consensus). F-SIFT is a SIFT algorithm operated in frequency domain not in spatial domain to escape using convolution operator for DoG and the rectangular kernel is used instead of Gaussian for feature extraction. B-RANSAC is an algorithm to avoid repetition and inequality of the selected sample in an image while extracted features are matched. The computational time is slightly reduced by using F-SIFT and the performance of image matching is increased by using B-RANSAC. These algorithms could bring a result of fast and reliable image matching. A series of simulation has been performed to verify the performance for image matching.
- KSP Keywords
- Computational time, Feature extractioN, Image Matching, Random sample consensus, SIFT Algorithm, frequency domain(FD), matching algorithm, scale invariant feature transform(SIFT), spatial domain