Component-Based License Plate Detection Using Conditional Random Field Model

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Component-Based License Plate Detection Using Conditional Random Field Model
	Li, Bo 1; Tian, Bin1 ; Li, Ye 1; Wen, Ding 2
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2013-12-01
卷号	14 期号:4 页码:1690-1699
文章类型	Article
摘要	This paper presents a novel algorithm for license plate detection in complex scenes, particularly for the all-day traffic surveillance environment. Unlike low-level feature-based methods, our work is motivated by component-based models for object detection. The detection process is divided into three steps, namely, decomposition, modeling, and inference. First, observing that one license plate is decomposed into several constituent characters, the maximally stable extremal region detector is used to extract candidate characters in images. Then, conditional random field (CRF) models are constructed on the candidate characters in neighborhoods. This way, the spatial and visual relationships among the characters is integrated in CRF in the form of probability distribution. Finally, the exact bounding boxes of license plates are estimated through the belief propagation inference on CRF. Both visual and structural features of license plates are fully exploited during detection. Hence, our approach can adapt to various environmental factors, such as cluttered background and illumination variation. A series of experiments are conducted on images that are collected from the actual road surveillance environment. The experimental results show the outstanding detection performance of the proposed method comparing with traditional algorithms.
关键词	Component-based Object Detection Computer Vision Conditional Random Field (Crf) License Plate Detection
WOS标题词	Science & Technology ; Technology
关键词[WOS]	OBJECT RECOGNITION ; LOCATION ; SYSTEMS
收录类别	SCI
语种	英语
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:000328048100013
引用统计	被引频次：54[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3642
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Natl Univ Def Technol, Ctr Mil Computat Expt & Parallel Syst Technol, Changsha 410073, Hunan, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Li, Bo,Tian, Bin,Li, Ye,et al. Component-Based License Plate Detection Using Conditional Random Field Model[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2013,14(4):1690-1699.
APA	Li, Bo,Tian, Bin,Li, Ye,&Wen, Ding.(2013).Component-Based License Plate Detection Using Conditional Random Field Model.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,14(4),1690-1699.
MLA	Li, Bo,et al."Component-Based License Plate Detection Using Conditional Random Field Model".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 14.4(2013):1690-1699.