Title :
Image Feature Detection and Matching Based on SUSAN Method
Author :
Muyun, Weng ; Mingyi, He
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
A new approach to image edge detection and feature matching is proposed. In which, the edge detection employs SUSAN (small univalue segment assimilating nucleus) method at low level image processing. And the integration feature matching is based on NMI (normalized moment of inertia) in combination with intensity and configuration information, achieving object recognition and tracking. The feature detection with SUSAN method locates precisely and not sensibly for local noise. NMI of image has translation invariability, rotation invariability and scale invariability. The simulated experimental results show that the algorithm is efficient for intensity variety, geometry aberration and some noise images
Keywords :
edge detection; feature extraction; image denoising; image matching; object recognition; optical tracking; SUSAN method; edge detection; feature matching; image feature detection; noise image; normalized moment of inertia; object recognition; object tracking; rotation invariability; scale invariability; small univalue segment assimilating nucleus; translation invariability; Computational efficiency; Computational geometry; Computer vision; Helium; Image edge detection; Image matching; Image processing; Image segmentation; Kernel; Laboratories;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.96
