DocumentCode :
2301171
Title :
Vehicle-logo Recognition Method Based on Tchebichef Moment Invariants and SVM
Author :
Dai, Shijie ; Huang, He ; Gao, Zhangying ; Li, Kai ; Xiao, Shumei
Author_Institution :
Res. Inst. of Robot. & Autom., Hebei Univ. of Technol., Tianjin, China
Volume :
3
fYear :
2009
fDate :
19-21 May 2009
Firstpage :
18
Lastpage :
21
Abstract :
In order to solve the problem about the recognition accuracy, Tchebichef moment invariants and support vector machine (SVM) are adopted to recognize the vehicle-logo. It extracts six invariant moments of the object as feature vectors, and then uses the support vector machines (SVM) to recognize vehicle-logo. Tchebichef moment invariants perform significantly better than Hu moment invariants and Zernike moment invariants. The result of these experiments suggests that this system has a high recognition rate in both noise-free and noisy environment which has high practical value.
Keywords :
automated highways; feature extraction; image recognition; method of moments; road vehicles; support vector machines; Hu moment invariant; SVM; Tchebichef moment invariant; Zernike moment invariant; feature vector extraction; object extraction; support vector machine; vehicle-logo recognition method; Licenses; Noise shaping; Polynomials; Redundancy; Robotics and automation; Shape; Software engineering; Support vector machines; Vehicles; Working environment noise; Support vector machines; Tchebichef moment invariants; vehicle-logo recognition (VLR);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, 2009. WCSE '09. WRI World Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3570-8
Type :
conf
DOI :
10.1109/WCSE.2009.263
Filename :
5319356
Link To Document :
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