A Improved Infrared and Visible Images Matching Based on SURF

Dong Mei Li; Jing Lei Zhang

doi:10.4028/www.scientific.net/AMM.325-326.1637

Paper Titles

Intelligent System of Brain Tumor Automation Diagnosis Based on Image Analysis and Mining
p.1619

The Research and Application of Association Rules Algorithm
p.1623

A K-Medoids Clustering Algorithm Based on Particle Swarm Algorithm with Simulated Annealing
p.1628

Rough Clustering Method Based on Particle Swarm Optimization Algorithm
p.1632

A Improved Infrared and Visible Images Matching Based on SURF
p.1637

Ultrasonic Image De-Noising Based on New Wavelet Threshold Function
p.1641

Improved Blind Equalization Algorithm and Simulation
p.1645

A Speech Endpoint Detection Based on Empirical Mode Decomposition and Average Magnitude Difference Function
p.1649

A Finger Vein Recognition Method Based on PCA-RBF Neural Network
p.1653

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 325-326A Improved Infrared and Visible Images Matching...

A Improved Infrared and Visible Images Matching Based on SURF

Abstract:

Images matching is the basis of image registration. For their difference, a improved SURF(speeded up robust features) algorithm was proposed for the infrared and visible images matching. Firstly, edges were extracted from the images to improve the similarity of infrared and visible images. Then SURF algorithm was used to detect interest points, and the dimension of the point descriptor was 64. Finally, found the matching points by Euclidean distance. Experimental results show that some invalid data points were eliminated.

You might also be interested in these eBooks

Manufacturing Engineering and Process II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 325-326)

Pages:

1637-1640

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.325-326.1637

Citation:

Cite this paper

Online since:

June 2013

Authors:

Dong Mei Li, Jing Lei Zhang

Keywords:

Edge Detection, Euclidean Distance, Matching, SURF

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Ruihua Liu, Yanguang Wang, SAR image matching based on speeded up robust feature[J]. Global Congress on Intelligent Systems, 2009:518-522.

DOI: 10.1109/gcis.2009.297

Google Scholar

[2] Bjing Wang, Dongliang Wu, Wenzheng Xu, Quan Lu, Fan Li, Shangqian Liu, Guowang Gao, Rui Lai. A new image registration method for infrared images and visible images[J]. International Congress on Image and Signal Processing, 2010:1745-1749.

DOI: 10.1109/cisp.2010.5647902

Google Scholar

[3] D. Lowe. Object recognition from local scale-invariant features[C]. International Conferenceon Computer Vision, Corfu, Greece, 1999:1150-1157.

Google Scholar

[4] H. Bay, T. Tuytelaars, and L. Van Gool. SURF:Speeded up robust features[C]. Proceedings of the European Conference on Computer Vision, 2006:404-417.

DOI: 10.1007/11744023_32

Google Scholar

[5] Hongwei Li, Binhai Wang. Research on the infrared and visible power-equipment image fusion for inspection robots[J]. International Conference on Applied Robotics for the Power Industry, 2010:1-5.

DOI: 10.1109/carpi.2010.5624441

Google Scholar

[6] Fecit Technology Research and Development Center. MATLAB6.5 Assisted image processing[M]. Beijing: Electronics Industry Press, 2003:184-188.

Google Scholar

[7] Yongming Wang, Guijin Wang. Image local invariant features and descriptors[M]. Beijing: National Defense Industry Press, 2010:89-141.

Google Scholar