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ANGADI INSTITUTE OF TECHOLOGY AND
MANAGEMENT
BELGAUM
VISION BASED REAL-TIME
SYSTEM FOR TRAFFIC
ANALYSIS
GROUP MEMBERS:
1.Mahaveer 2.Suraj C.
3.Mahesh P.
INTRODUCTION:
• Traffic problems nowadays are increasing because of
growing number of vehicles.
• Automatic traffic monitoring and surveillance are
important for traffic usage and management.
• traffic control techniques are
1.magnetic loop 2. infra-red and radar sensors
• It is well recognized that vision-based camera system
are more versatile for traffic parameter estimation.
• Image tracking of moving vehicles can give us
quantitative description of traffic flow.
WHY TRAFFIC ANALYSIS
NECESSARY?
• Fundamental importance for traffic operation,
pavement design, enhance public safety and
transportation planning.
• Highway Capacity Manual requires adjustments
to heavy-vehicle volumes in capacity analysis.
PROPOSED SYSTEM:
• It is a prototype design
and development of
vision based real-time
vehicle counting &
classification system.
• The system will detect
vehicles through video.
• The video will then be
analyzed for vehicle
detection &
classification.
• The system contains
PROPOSED METHODS:
1.VEHICLE COUNTING:
1.Background estimation
2.Thresholding
3.Vehicle detection
• When vehicle enters into the ROI the
vehicle is counted by Vision system once.
• The proposed vision system is able to
count the total number of vehicles which
pass through the ROI.
• Vehicle passed in lane can be estimated.
2.VEHICLE CLASSIFICATION:
• The detected vehicle is sent to blob analysis
method in which statistical features are
extracted to classify vehicles.
• The data will be saved on database for further
use or analysis.
• Thresholding is performed in order to obtain
presence/absence of information.
THE PROPOSED SYSTEM
CONTAINS:
• User login :User on site
• Administrator login :Database change
• Video preview : Video information
• Camera calibration: Region of interest
• Camera control :Brightness, contrast and color
• Process start and stop
• Process scheduler: Predefined time
• Report generation: Report in excel or pdf
format.
• Option to create Image database of detected
vehicles
• Video save option
PROJECT OUTCOMES:
• Count of vehicle
• Type of vehicle (bus, car)
• Time at which vehicle passed on the road.
• Image database of detected vehicles
• Report generation in .pdf/.xls
ADVANTAGES OF
PROPOSED SYSTEM:
• Vehicle count.
• Vehicle classification.
• Provides more traffic information.
• Easily installable.
• Easy maintenance.
• Low cost.
Future implement
• Occlusion detection.
• Light reflection should be investigated and
explored to enhance the reliability of the system.
• Speed of vehicle can be measured.
Future implement
• Improve the algorithm to work in night and all
weather conditions.
• Traffic jam prediction.
• License plate recognition system to be
embedded in the algorithm.
Final report

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Final report

  • 1. ANGADI INSTITUTE OF TECHOLOGY AND MANAGEMENT BELGAUM VISION BASED REAL-TIME SYSTEM FOR TRAFFIC ANALYSIS GROUP MEMBERS: 1.Mahaveer 2.Suraj C. 3.Mahesh P.
  • 2. INTRODUCTION: • Traffic problems nowadays are increasing because of growing number of vehicles. • Automatic traffic monitoring and surveillance are important for traffic usage and management. • traffic control techniques are 1.magnetic loop 2. infra-red and radar sensors • It is well recognized that vision-based camera system are more versatile for traffic parameter estimation. • Image tracking of moving vehicles can give us quantitative description of traffic flow.
  • 3. WHY TRAFFIC ANALYSIS NECESSARY? • Fundamental importance for traffic operation, pavement design, enhance public safety and transportation planning. • Highway Capacity Manual requires adjustments to heavy-vehicle volumes in capacity analysis.
  • 4. PROPOSED SYSTEM: • It is a prototype design and development of vision based real-time vehicle counting & classification system. • The system will detect vehicles through video. • The video will then be analyzed for vehicle detection & classification. • The system contains
  • 5. PROPOSED METHODS: 1.VEHICLE COUNTING: 1.Background estimation 2.Thresholding 3.Vehicle detection • When vehicle enters into the ROI the vehicle is counted by Vision system once. • The proposed vision system is able to count the total number of vehicles which pass through the ROI. • Vehicle passed in lane can be estimated.
  • 6. 2.VEHICLE CLASSIFICATION: • The detected vehicle is sent to blob analysis method in which statistical features are extracted to classify vehicles. • The data will be saved on database for further use or analysis. • Thresholding is performed in order to obtain presence/absence of information.
  • 7. THE PROPOSED SYSTEM CONTAINS: • User login :User on site • Administrator login :Database change • Video preview : Video information • Camera calibration: Region of interest • Camera control :Brightness, contrast and color
  • 8. • Process start and stop • Process scheduler: Predefined time • Report generation: Report in excel or pdf format. • Option to create Image database of detected vehicles • Video save option
  • 9. PROJECT OUTCOMES: • Count of vehicle • Type of vehicle (bus, car) • Time at which vehicle passed on the road. • Image database of detected vehicles • Report generation in .pdf/.xls
  • 10. ADVANTAGES OF PROPOSED SYSTEM: • Vehicle count. • Vehicle classification. • Provides more traffic information. • Easily installable. • Easy maintenance. • Low cost.
  • 11. Future implement • Occlusion detection. • Light reflection should be investigated and explored to enhance the reliability of the system. • Speed of vehicle can be measured.
  • 12. Future implement • Improve the algorithm to work in night and all weather conditions. • Traffic jam prediction. • License plate recognition system to be embedded in the algorithm.