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