Chen, Hao Department of Transportation Engineering,

© 2008 Chen Hao, Beijing Institute of Technology1

Intelligent Parking System: Parking Guide Application in Beijing and Method for

License Plate Localization

Chen, HaoDepartment of Transportation Engineering,

Beijing Institute of Technology, Beijing, PR China. [email protected]

http://chenhaoits.cn

2© 2008 Chen Hao, Beijing Institute of Technology

Basic Information Our lab

Department of Transportation Engineering School of Mechanical & Vehicular Engineering

• Four research teamsTraffic Plan and DesignTraffic Information and ManagementLogistic OperationAutomobile Application

Me• B.S., Transportation Engineering, Beijing Institute of Technology, China. 2005

Paper: Public Transportation Query System of Beijing • M.S., Transportation Engineering, Beijing Institute of Technology, China, 2007

Thesis: Research and Application of License Plate System

• Research Assistant in the Intelligent Transportation Lab• Research Interests:

Intelligent Transportation Systems, Image Processing and Pattern Recognition, GIS, Dynamic Traffic Assignment, Traffic Modeling and Simulation, Pavement Design.


Outline： Parking Guide System A project of our lab (demonstrated by the government for 2008

Olympic Games in Beijing )

License Plate Recognition System Mainly introduce the plate localization process: correlation based method

• Brief Introduction• Candidate Area Extraction • Candidate Verification • Experimental results


1. Parking Guide System• Circumstance

The parking lots of Cui Wei shopping mall in BeijingTwo floors, 267 parking spaces

• Functions:Automatic parking guideEasily Management for employees Alleviate traffic pressure on the road

• Three Key TechnologiesUltrasonic DetectorCAN Bus Communication LED Billboard


Layer Components• Data Collection Layer

the basic layercollect the data from all parking spaces

• District Layergather the data from Parking Space Detectore.g. one District Collector connect with 60 detectors

• Floor Layerfloor layer controls all data from the corresponding district collectors

• Central Layerall data input to the central collectorinformation broadcasting


Framework of Our Parking Guide System

Floor Controller


Parking Space Detector

Central Controller

District Controller


2. License Plate Recognition System 2.1 Brief Introduction• Three parts

license plate localization candidate extraction candidate verification

character segmentationcharacter recognition

• Difficultiesweather, illuminationlicense plate: size, colorshoot anglepollution and abrasionshelter problem High quality camera and image processing board

(arithmetic embedded in a digital processing chip)


plate localization

character normalization and recognition

character segmentation

An Example:


2.2 Candidate Area Extraction

• Preprocessing and Rank Filter• Searching Reference Lines • Get candidate areas

(a)

(d) (e)

(b) (c)


• Auto-Correlation Based Algorithm:

Auto-correlation algorithm; (a) calculate the auto-correlation

property; (b) auto-correlation curve;

Base on the characteristic that plate area has seven block areas.

The auto-correlation curve has about thirteen peaks for the car plate.

2.3 Candidate Verification

(a)(b)


• Projection Based Algorithm:

Verify the car plate using projection

algorithmVerify the headlight

area using projection algorithm


Framework of proposed candidate verification method. In our experiment, th1=7, th2=20, th3=5, th4=20.


• Step 1: Extract plate which has light characters in dark background.

• Step 2: Extract plate which has dark characters in light background.


• Step 3: Extract blue-white plate which has polluted by the light at night.


2.4 Experimental results• Database

– 720*280 JPEG color images from a park entrance

– 1704 images from three days surveillance are tested

• Results– [1] : 88.1%

– Proposed: 97.5%

Algorithms Images Correct No Plate

[1] 1704 1501 188

Proposed 1704 1661 21

[1] V. Shapiro, G. Gluhchev, D. Dimov, Towards a multinational car license plate recognition system, Machine Vision Application, Volume 17, Issue 3, July 2006. pp. 173 – 183


Thanks for your attention!

Q&A

Chen, Hao Department of Transportation Engineering,

Documents

Transcript of Chen, Hao Department of Transportation Engineering,