Paper Info
Title
An integrative approach to accurate vehicle logo detection
Abstract
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.
Year
DOI
Venue
2013
10.1155/2013/391652
J. Electrical and Computer Engineering
Keywords
Field
DocType
vehicle region detection,vehicle recognition,vehicle logo detection,small logo target,integrative approach,proposed scheme,reliable vehicle logo detection,segmented roi,prelogo detection step,accurate vehicle logo detection,precise logo positioning,frontal vehicle image
Computer vision,Adaboost algorithm,AdaBoost,Computer science,Segmentation,Support vector machine,Logo,Visual attention,Artificial intelligence,Intelligent transportation system,Region detection
Journal
Volume
ISSN
Citations 
2013,
2090-0147
0
PageRank 
References 
Authors
0.34
20
2
Name
Order
Citations
PageRank
Hao Pan1466.94
Bai-ling Zhang251750.49