Automated traffic control by using image processing

Automated Traffic Control By Using Image Processing  Course Instructor: RETHWAN FAIZ  Group members: 1. Banik, Swarnasree (14-25570-1) 2. Kazi, Tasnim (14-25738-1) 3. Himo,Aqib Shahariar (14-25680-1) 4. Athy,Honey alam (14-26376-1) 1

Contents  Introduction  Steps of image processing  Earlier Research  Automatic controlling method of traffic light  Edge detection  Algorithm  Future Work  Advantages  Conclusion 2

3 Introduction As the world is growing older, life is also getting tougher. People are increasing with huge number despite the fact that lands are not increasing and so traffic jam too. In modern life time is really very expensive and major of our times are being killed by traffic jam. It is said that ratio of cars with respect to roads, the irrational distribution of the buildings, lack of experience of traffic police are the main reasons for traffic jam. This problems can be sorted out by making some good decision on infrastructure, limiting numbers of signals and introducing some new technique on traffic controlling system. This techniques are briefly described in the next part of our writings.

What is Image processing?  Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it.  It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image.  Image Processing system includes treating images as two dimensional signals while applying already set signal processing methods to them. 4

Steps of image processing: 1.Importing the image with optical scanner or by digital photography. 2.Analyzing and manipulating the image which includes data compression and image enhancement and spotting patterns that are not to human eyes like satellite photographs. 3. Output is the last stage in which result can be altered image or report that is based on image analysis. 6

Block Diagram: 7 REFERENCE IMAGE RGB TO GRAY CONVERSION IMAGE RESIZING IMAGE ENHANCEMENT EDGE DETECTION CAPTURED IMAGE RGB TO GRAY CONVERSION IMAGE RESIZING IMAGE ENHANCEMENT EDGE DETECTION IMAGE MATCHING TIMING ALLOCATION

Earlier Research : 1. In early 1920s Bartlane cable picture transmission system used to transmit newspaper images across the Atlantic, though the images were coded. 2. After 1920s-improvements were made to the Bartlane system resulted in higher quality images with the increased number of tones in reproduced images. In 1960s: Improvements in computing technology and the onset of the space race led to a surge of work in digital image processing. 3. In 1964: computers used to improve the quality of images of the moon taken by the Ranger 7 probe Such techniques were used in other space missions including the Apollo landing. 4. 1970s, digital image processing begins to be used in medical applications. In 1979, Sir Godfrey N. Hounsfield & Prof. Allan M. Cormack share the Nobel Prize in medicine for the invention of tomography, 5. 1980s - Today: The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas 8

Objective of this Work :  The project proposed a system for controlling the traffic light by image processing.  In this system the vehicles are not being detected by sensors, rather it is detected by images.  In this process initially the system will have picture of the empty road. And the system will continuously take pictures of the road and will compare those with the empty ones which will give signal of the density of vehicles present on the road.  By detecting the density of the vehicles, light will glow, controlling the traffic. Since it will take the actual picture of the road, there will be very light chance of glowing the green signal when the road is empty. 9

Automatic controlling method of traffic light:  Automatic traffic controllers are also known as traffic light control. These basically consist of 3 different colored lights, a sensor and a timer which turn ON and OFF at each interval.  The purpose of the sensor is to capture the availability of the vehicles. In has the ability to decide the present and absence of the traffic even the density of the traffic on a road.  It can also compare the traffic with other intersection and provide signaling message. The automatic controlling is 24/7 on service unlike traffic police for at max 12 hours. Minor or little effect on the weather changes. 10

Edge detection :  Most of the information about the shape of an image are located in edges. The other benefits of edge detection is not taking more space in computer memory. This technique reduces the image size and filters out important information.  There are many techniques available for edge detection. These are-  1. Prewitt edge detection technique.  2. Sobel edge detection technique.  3. Roberts edge detection technique.  4. Zerocross threshold edge detection technique.  5. Canny edge detection technique.  We have chosen the canny edge detection technique for its many advantages 11

Algorithm:  If the matching is between 0 to 20% - red light is on for 90 seconds.  If the matching is between 20 to 40% - green light is on for 20 seconds.  If the matching is between 40 to 70% - green light is on for 30 seconds.  If the matching is between 70 to 90% - green light is on for 60 seconds.  If the matching is between 90 to 100% - green lightis on for 90 seconds. 12

Matching Between 100 to 90 Percentage 15

Future Work:  Edge detecting from videos: The whole procedure can be done through a captured image as well as through a video. By creating algorithm through image processing edges of vehicles will be detected.  Weather consideration: In this project, weather was not considered. So when there is fog it might not get the accurate results and provide proper signaling message. Also, at night this type of problems may occur. So, in future research on Image Processing can be done with the consideration of weather by edge detecting.  Hardware Implementation: If this method can be implemented in hardware than it will be a very useful system. 18

Advantages  More Convenience  Energy Management & Savings  Easy to detect than sensors  Low cost 19

Potential problems 1.Hacking 2.Power consumption 3.Reduce of human interaction 4.Problems in microcontroller. 5.Problems detecting the image properly in foggy weather. 20

Conclusion Traffic control system we introduced in this project, we overcome all the difficulties that earlier traffic control systems had. Previously, traffic control systems were built with timer. So, this process is a solution for the previous systems. 21

References  http://www.engineersgarage.com/articles/image-processing-tutorial- applications  http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?reload=true&punumber =83  https://sisu.ut.ee/dev/imageprocessing/book/1 22

Automated traffic control by using image processing

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Automated traffic control by using image processing