Real Time Traffic Density Count using Image Processing

Abbas, Naeem; Tayyab, Muhammad; Qadri, Muhammad Yasir

doi:10.5120/14476-2736

Cited by 22 publications

(9 citation statements)

References 5 publications

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“…Identifikasi wajah saat ini juga sudah banyak diaplikasikan pada sistem absensi menggantikan sistem absensi manual dan juga sistem absensi dengan sidik jari [6] pada perusahaan yang memprioritaskan keamanan. Selain pada bidang medis dan sistem keamanan, teknologi pengolahan citra juga sudah diaplikasikan pada sistem lalu lintas salah satunya untuk mendeteksi kepadatan lalu lintas pada persimpangan jalan [7] juga mendeteksi pelanggaran dalam berlalu lintas [8]. Sistem pendeteksian nomor plat kendaraan sudah dibuat diberbagai Negara namun dengan format yang berbeda, karena setiap Negara memiliki format plat nomor kendaraan masing-masing, misalnya saja sistem pendeteksian nomor plat kendaraan dengan format Mesir yang dibuat oleh Khalil [9] .…”

Section: B State Of Artunclassified

Detection of Vehicles Number Plate Using Image Processing with Template matching Method

Sarief

Biu²,

Harismana³

et al. 2019

Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan

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To design a system in order to identify an object number plate for the Indonesian format, an initial system is designed, in the form of a vehicle licence plate recognition application using template matching method. The goal of this application is to be implemented to the parking system by identifying the number plate. This system uses the camera for the image capture process, by utilizing image processing technology with the matching correlation template method for recognition to produce a string value from the image. Before doing recognition process, First, the pre processing stage is performed on the input image which includes grayscale, binary, until the segmentation stage before the correlation / comparison process is carried out on the image of Template. The process that occure in the pre-processing unit done for some reason including to make the image lighter and less complex. This process will make the image easer to be processed and also to increase the proses speed of the system. Before aply template matching algorithm to the image output from segmentation process, the image has to be resized first to match the size of the template image stored in data base. This has to done so that the target image and the template image can be match directly with template matching algorithm. The output of this system is a string value which is refer to the value of the license plate capture by camera used by the system. The problem that arises in the introduction process is how to identify various types of characters with various sizes and shapes so that the string value is the same as the text image. The average success rate of this application is 70% so that further research must be carried out so this system can be implemented into the parking system. Keyword : Image Processing, Template matching, Camera, Number Plate, Matlab

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Section: B State Of Artunclassified

Detection of Vehicles Number Plate Using Image Processing with Template matching Method

Sarief

Biu²,

Harismana³

et al. 2019

Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan

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“…A. and Mishra D., 2015) Several researches have been done for controlling traffic using different techniques of image processing. They are mainly based on vehicle counting methods (Aher C. and Shaikh S.,2015), (Abbas N., et al, 2013) (Niksaz P., 2012) and image comparison methods. (Choudekar P. et al,2011) The aim of this research is to identify a technologically advanced, intelligent traffic controlling method by recognizing the actual area of the traffic which is presented on a road thereby providing an adequate amount of time for the traffic to pass by dynamically changing traffic light timers.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Traffic Light Controlling System According to the Traffic Area

Fernando

Jayasiri

2019

Kalyani: J. Univ. Kelaniya

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Traffic congestion is a significant problem in recent years because of the everincreasing number of vehicles in the roads and the poor management of traffic. Traffic congestions are not constant throughout the day. They are changing from time to time. Present traffic controllers have fixed time intervals for red, yellow and green signal lights and therefore, cannot provide a better solution for the dynamic traffic congestion during the day. Computer vision technology can be used to create an intelligent traffic controlling system which can adapt its time intervals according to the real traffic. In the existing traffic controlling systems, a wastage of the green signal duration occurs as fixed green signal duration assigned for a phase is sometimes larger than the actual requirement. Hence, the other roads at the intersection have to wait, in vain, with more traffic, until that fixed green time period is over. In the proposed method, real time traffic image sequences are analyzed by using image processing in order to obtain the actual traffic area. Then, time for green light is assigned according to that traffic area. Hence, the wastage of green signal duration is eliminated by the proposed method since it allocates time for the green signal that is sufficient for the actual traffic

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“…This research yielded an accuracy of 97% [1]. A similar research is on the use of image processing to calculate traffic density [2][3][4]. Traffic management based on artificial neural network has also been developed by researchers with the use of prediction function of traffic congestion [5].…”

Section: Introductionmentioning

confidence: 99%

Automatic vehicle counting using background subtraction method on gray scale images and morphology operation

Adi

Widodo

et al. 2018

J. Phys.: Conf. Ser.

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Abstract. Traffic monitoring on road needs to be done, the counting of the number of vehicles passing the road is necessary. It is more emphasized for highway transportation management in order to prevent efforts. Therefore, it is necessary to develop a system that is able to counting the number of vehicles automatically. Video processing method is able to counting the number of vehicles automatically. This research has development a system of vehicle counting on toll road. This system includes processes of video acquisition, frame extraction, and image processing for each frame. Video acquisition is conducted in the morning, at noon, in the afternoon, and in the evening. This system employs of background subtraction and morphology methods on gray scale images for vehicle counting. The best vehicle counting results were obtained in the morning with a counting accuracy of 86.36 %, whereas the lowest accuracy was in the evening, at 21.43 %. Differences in morning and evening results are caused by different illumination in the morning and evening. This will cause the values in the image pixels to be different.

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Real Time Traffic Density Count using Image Processing

Cited by 22 publications

References 5 publications

Detection of Vehicles Number Plate Using Image Processing with Template matching Method

Detection of Vehicles Number Plate Using Image Processing with Template matching Method

Intelligent Traffic Light Controlling System According to the Traffic Area

Automatic vehicle counting using background subtraction method on gray scale images and morphology operation

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