An Integrative Approach to Accurate Vehicle Logo Detection
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-27
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Engineering Sciences and Information Technology
Information Technology and Computer Science
Abstract EN
Vehicle logo detection from images captured by surveillance cameras is an important step towards the vehicle recognition that is required for many applications in intelligent transportation systems and automatic surveillance.
The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination.
A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision.
Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target.
An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles.
An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images.
A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM), resulting in precise logo positioning.
Extensive experiments were conducted to verify the efficiency of the proposed scheme.
American Psychological Association (APA)
Pan, Hao& Zhang, Bailing. 2013. An Integrative Approach to Accurate Vehicle Logo Detection. Journal of Electrical and Computer Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-468453
Modern Language Association (MLA)
Pan, Hao& Zhang, Bailing. An Integrative Approach to Accurate Vehicle Logo Detection. Journal of Electrical and Computer Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-468453
American Medical Association (AMA)
Pan, Hao& Zhang, Bailing. An Integrative Approach to Accurate Vehicle Logo Detection. Journal of Electrical and Computer Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-468453
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-468453