modeling design and analysis of intelligent traffic control system based on statistical image...

Modeling, Design and Analysis of Intelligent Traffic Control System Based on Integrated Statistical Image Processing Techniques

Yasar Abbas Ur RehmanDepartment of Electrical EngineeringCity University PeshawarFAST, NUCES Peshawar Campus

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Outline•Introduction•Problem Statement•Proposed Solution•Results •Conclusion

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Introduction•Monitoring and control of intercity traffic

▫Not a trivial problem▫Careful planning▫Increase in road infrastructure?▫Availability of Technological Assets

•Camera controlled monitoring and control▫Vehicle flow▫Speed calculation▫Automatic Number Plate Recognition (ANPR)▫Crash detection

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Problem Statement•Detection Problem

▫Presence and absence of vehicle▫No background information

•Design of Autonomous System for Traffic▫Detection ▫Classification▫Display

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Proposed Solution•Detection Problem

▫Background Modeling

(1)

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Vehicle Detection

(2)

(3)

  (4) 

(5) To simplify calculations, we make a use of histogram and relate it with the above equations: 

(6) 

(7)

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Cont. (8)

  (9)

  (10)

(11)

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System Design •Vehicle Detection System (VDS)•Vehicle Counting and Classification

System (VCCS)•Traffic Signals Control System (TSCS)•Data Display System (DDS)

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Cont.•System Interconnection

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VDS• Probability Based Vehicle Detection (PBVD)

Algorithm▫ Frame acquisition▫ Vehicle appearance

(10)

(11)

▫ Vehicle extraction▫ Maximum area calculation

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VCCS•Vehicle labeling•Classification of vehicles

▫Small▫Medium▫Large

•Send vehicle statistics to ▫TSCS▫DDS

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TSCS•Vehicle comparison for both lanes•If same number of vehicles

▫Assign equal timing to both lanes

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DDS•Display total number of vehicles•Number of pixels each vehicle contain•Vehicle category•Green signal for road

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Experimental Results•Background update parameter

▫α = 1 × 10-3

•Threshold for vehicle appearance▫t = 300

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Cont..

Prototype of Proposed System

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Cont.

Data Display System (DDS)

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Cont.

a) Image of empty road b) image of the road containing car c) image enhancement after median filtering d) image after frame subtraction

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Cont.

a) Image after edge detection b) Binary dilation c) Binary Hole Filling d) Binary Erosion

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Cont.

a) Area Calculation b) Final Result (Detected Objects)

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Cont.

Current frame

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Cont.

Frame subtraction

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Cont.

Edge detection and binary dilation

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Cont.

Resultant image after binary hole filling,

erosion and area calculation

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Cont.

Final result

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Cont..

0 50 100 150 200 2500

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10

15

20

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Pixel intensities

Abs

olut

e di

ffer

ene

Spred after absolute histogram subtraction

Spread after absolute histogram subtraction

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Conclusion•Traffic control system for

▫Monitoring▫Control of intercity traffic

•Prototype testing▫Accurate results

•Real time testing▫Satisfactory results▫Morphological operators need control▫Need of restoration techniques

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Question