CSE DEPARTMENT

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

TRAFFIC JAM DETECTION USING IMAGE PROCESSING

ABSTRACT:1. To control traffic management image processing

has been introduced2. 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

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 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

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 usedDRAWBACKS:• These detectors need separate system for traffic

detection & surviallance• Detectors failure rate is more in poor road surfaces• Fails in different climatic conditions

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

PROCEDURE:• KEYPOINTS ARE:

1. Image analysis2. Object detection3. Typed object count4. Motion detection5. Result representation

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:

PHASE II: Two operations used here:1. Erosion2. Dilation

EROSION:• It decreases the size of objects & removes

disturbances in the image

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 detection2. 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

PROPOSED SYSTEM:Architecture consists of 5 components:1. Traffic management2. Roadway system3. Server 4. Android application5. Camera

ARCHITECTURE:

ADVANTAGES: This technique is cost-effective , reliable & flexibleFree flow of trafficGives an opportunity for the user to reach the destination in less time

They provide more traffic information,combine both surveillance and traffic control technologies

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

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