[an error occurred while processing this directive] [an error occurred while processing this directive]
[an error occurred while processing this directive]Journal of Projectiles, Rockets, Missiles and Guidance >
Infrared and Optical Image Matching Algorithm Based on Complementary Features
Received date: 2011-01-13
Online published: 2025-05-30
In view of the big gray difference in multi-sensor image, and classical SIFT algorithm is prone to cause the error match; a method of adopting complementary features for matching was presented. During feature detection, the DoG detector was combined with Harris-Laplace detector to detect the blob-like and corner-like structure. In order to decrease the error matching caused by overabundance feature of DoG, searching features in bigger areas and the feature distribution was improved. The experimental result shows that the matching points increase effectively and the correct matching ratio is improved.
Key words: SIFT; DoG; Harris-Laplace; matching
ZHOU Wei , LIU Feng , LIU Jing . Infrared and Optical Image Matching Algorithm Based on Complementary Features[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2011 , 31(5) : 29 -32 . DOI: 10.15892/j.cnki.djzdxb.2011.05.023
| [1] | Thourn K, Kitjaidure Y. Multi-view shape recognition based on principal component analysis [C]// Advanced Computer Control, ICACC'09, 2009: 265-269. |
| [2] | Lowe DG. Distinctive image features from scale-Invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91-10. |
| [3] | Song R, Szymanski J. Well-distributed SIFT features[J]. Electronics Letters, 2009, 45(6): 308-310. |
| [4] | Mikolajczyk K, Schmid C. Scale and affine invariant interest point detectors[J]. International Journal of Computer Vision, 2004, 60(1): 63-86. |
| [5] | Harris Stephens M. A combined corner and edge detector [C]// Alvey88, 1988: 147-152. |
| [6] | Lowe DG. Local feature view clustering for 3D object recognition [C]// Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2001. |
/
| 〈 |
|
〉 |