Vehicle logo recognition by weighted multi‐class support vector machine ensembles based on sharpness histogram features-Reference-Cited by-同舟云学术

Vehicle logo recognition by weighted multi‐class support vector machine ensembles based on sharpness histogram features

Published:2015-07 Issue:7 Volume:9 Page:527-534
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Xiao Jianli¹,Xiang Wenshu²³,Liu Yuncai²³

Affiliation:

1. Shanghai Keylab of Modern Optical System, and Engineering Research Centre of Optical Instrument and System, Ministry of EducationUniversity of Shanghai for Science and TechnologyNo. 516 Jun Gong RoadShanghai200093China

2. Department of AutomationShanghai Jiao Tong UniversityShanghai200240People's Republic of China

3. Key Laboratory of System Control and Information Processing, Ministry of Education of ChinaShanghai200240People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2014.0691

Reference28 articles.

1. A Gaussian mixture model and support vector machine approach to vehicle type and colour classification

2. 2014 IET Intelligent Transport Systems Z. Chen T. Ellis Semi‐automatic annotation samples for vehicle type classification in urban environments

3. Comparison of different wavelets for automatic identification of vehicle license plate

4. Robust license-plate recognition method for passing vehicles under outside environment

5. Vehicle logo recognition using a SIFT‐based enhanced matching scheme;Psyllos A.;IEEE Trans. Intell. Transp. Syst.,2010

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