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TRAFFIC JAM DETECTION USING IMAGE PROCESSING

PRESENTED BY
D.M.V.S.SAI
10F81A0586

CSE DEPARTMENT
ABSTRACT:
1. To control traffic management image processing has been
introduced
2. Easy to calculate traffic density which...
CONTENTS:
• Introduction
• Existing methods
• What is image processing?
• procedure
• Proposed system
• conclusion
INTRODUCTION:
• Works with latest technologies like digital image processing
• System consists of cameras that monitors tr...
EXISTING METHODS:
• Magnetic loop detectors are used to count number of vehicles
using magnetic properties
• Inductive loo...
WHAT IS IMAGE PROCESING?
• Image processing is the process of taking captured images as
binary data as primary input
• The...
PROCEDURE:
• KEYPOINTS ARE:

1.
2.
3.
4.
5.

Image analysis
Object detection
Typed object count
Motion detection
Result re...
PHASES OF IMAGE PROCESSING:
PHASE I:
• Videos frames extracted are converted into gray scale
• Any color that converts to ...
PHASE II:
 Two operations used here:
1. Erosion
2. Dilation
 EROSION:
• It decreases the size of objects & removes distu...
 DILATION:
• It increases the size of objects by filling the holes & broken
areas in the image by connecting them
PHASE III:
 Two operations used here:
1. Motion detection
2. Vehicle detection
 Motion detection:
• Here two consecutive...
PROPOSED SYSTEM:
Architecture consists of 5 components:
1. Traffic management
2. Roadway system
3. Server
4. Android appli...
ARCHITECTURE:
ADVANTAGES:
 This technique is cost-effective , reliable & flexible

Free flow of traffic
Gives an opportunity for the ...
CONCLUSION:
 Image processing is a better technique to control traffic jam

 It is more consistent in detecting vehicles...
REFERENCES:
• Zehang sun, george bebis, and Ronald Miller, “ on-road
vehicle detection using evolutionary gabor filter
opt...
Traffic jam detection using image processing
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Traffic jam detection using image processing

  1. 1. TRAFFIC JAM DETECTION USING IMAGE PROCESSING PRESENTED BY D.M.V.S.SAI 10F81A0586 CSE DEPARTMENT
  2. 2. ABSTRACT: 1. To control traffic management image processing has been introduced 2. Easy to calculate traffic density which is cost-effective 3. Image processing can detect vehicles in any climatic conditions 4. Using the information given by image processing technique, an android application is developed, which the user will get traffic density at location of his choice
  3. 3. CONTENTS: • Introduction • Existing methods • What is image processing? • procedure • Proposed system • conclusion
  4. 4. INTRODUCTION: • Works with latest technologies like digital image processing • System consists of cameras that monitors traffic by capturing videos • Extracts video frames at regular intervals and frames are compared to determine whether there is traffic jam or not • Android application which was developed will give the list of locations from database having density of traffic
  5. 5. EXISTING METHODS: • Magnetic loop detectors are used to count number of vehicles using magnetic properties • Inductive loop detectors provide cost effective solution • Light beams like IR,LASER are used DRAWBACKS: • These detectors need separate system for traffic detection & surviallance • Detectors failure rate is more in poor road surfaces • Fails in different climatic conditions
  6. 6. WHAT IS IMAGE PROCESING? • Image processing is the process of taking captured images as binary data as primary input • The captured digital images are processed that consists of elements of location & value called as picture elements • Operations of image processing are sharpening,blurring,brightening
  7. 7. PROCEDURE: • KEYPOINTS ARE: 1. 2. 3. 4. 5. Image analysis Object detection Typed object count Motion detection Result representation
  8. 8. PHASES OF IMAGE PROCESSING: PHASE I: • Videos frames extracted are converted into gray scale • Any color that converts to grayscale must obtain values from red,blue,green(RGB) colors • The greyscale image is then converted to binary • RGB to greyscale conversion is as follows:
  9. 9. PHASE II:  Two operations used here: 1. Erosion 2. Dilation  EROSION: • It decreases the size of objects & removes disturbances in the image
  10. 10.  DILATION: • It increases the size of objects by filling the holes & broken areas in the image by connecting them
  11. 11. PHASE III:  Two operations used here: 1. Motion detection 2. Vehicle detection  Motion detection: • Here two consecutive frames are taken & their histograms are compared with their threshold value • The motion of the image is detected by selecting an appropriate threshold value  Vehicle detection: • The profile of the roads is divided into sub-profiles • The length of the sub-profiles should be equivalent to length of the vehicle
  12. 12. PROPOSED SYSTEM: Architecture consists of 5 components: 1. Traffic management 2. Roadway system 3. Server 4. Android application 5. Camera
  13. 13. ARCHITECTURE:
  14. 14. ADVANTAGES:  This technique is cost-effective , reliable & flexible Free flow of traffic Gives an opportunity for the user to reach the destination in less time They provide more traffic information,combine both surveillance and traffic control technologies
  15. 15. CONCLUSION:  Image processing is a better technique to control traffic jam  It is more consistent in detecting vehicles presence as it visualizes actual traffic frames  Overall the system is good, but it still needs improvement to achieve hundred percent accuracy
  16. 16. REFERENCES: • Zehang sun, george bebis, and Ronald Miller, “ on-road vehicle detection using evolutionary gabor filter optimization” Mar-Apr 2012 • Khan muhammed nafee Mostafa, qudrat-E-alahy Ratul, “Traffic jam detection system”,pp 1-4 • Traffic safety facts, US Department of Transport, december 2012,pp 1-2
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its a ppt on traffic jam detection using image processing

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