Abstract
To sove the problem that correct match points cannot be effectively extracted in the match point purification links of current image matching algorithms, mRANSAC (multi-RANSAC) multi-transformation matrix method is proposed. Matching points cannot accurately correspond to each other due to the digital image's discrete sample style. There exist intrinsic position errors, and the corresponding transform matrices are different. Therefore, one transformation matrix cannot contain all the correctly matched points. The research results of RANSAC show that in the sets of non-maximal inner point number, enough points can induce correct matches, which can also be confirmed by the fact that different objective images result in different match numbers. Therefore, multi-transformation matrix is used to increase the matching point number and improve the purification efficiency. Three strategies, the set union method, the set extract method and the adaptive number threshold of inner point method are proposed. The purification results of mRANSAC are generally 60% to 300% more than those of RANSAC. Through setting suitable threshold value of mRANSAC, the purification rate can reach approximately 100%. This method can also be applied to solve the similar purification problem in other fields.
Original language | English |
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Pages (from-to) | 163-167 |
Number of pages | 5 |
Journal | Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) |
Volume | 43 |
Issue number | SUPPL.I |
DOIs | |
Publication status | Published - Jul 2013 |
Keywords
- Image matching
- Matching point purification
- RANSAC (random sample consensus)
- Transformation matrix