DocumentCode :
2827452
Title :
Multi-scale analysis and fractal signature (MSFS): A new approach to invariant corner extraction for image registration
Author :
Gao, Feng ; Wen, Gongjian ; Hui, Bingwei ; Lu, Huanzhang
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Volume :
3
fYear :
2010
fDate :
21-24 May 2010
Abstract :
Corner that is invariant to geometry transform and illumination change is a very important feature for image registration and target recognition etc. Corners extracted using intensities directly are robust, but with poor property in localization. Corners extracted by edge information are invariant to geometry transform and outstanding in localization, but not robust. Therefore in this paper, an algorithm is designed for corner extraction, which combines fractal signature, edge information and multi-scale analysis. The proposed algorithm is divided into four steps: firstly, extract edges from the image; secondly, compute the properties and prominent values of every point on the edge; thirdly, extract satisfactory corners using non-maximal suppress; finally, compute the descriptor of extracted points. The experiment results show that the proposed algorithm is robust to scale, rotation and illumination, and has good property in localization.
Keywords :
edge detection; fractals; image registration; transforms; edge information; fractal signature; geometry transform; illumination change; image registration; invariant corner extraction; multiscale analysis; target recognition; Algorithm design and analysis; Data mining; Fractals; Image analysis; Image registration; Information analysis; Information geometry; Lighting; Robustness; Target recognition; corner; edge; fractal; invariant; multi-scale; signature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
Type :
conf
DOI :
10.1109/ICFCC.2010.5497506
Filename :
5497506
Link To Document :
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