Traffic light control utilizing queue length and object segmentation
Other Title(s)
التحكم بالإشارة الضوئية من خلال استعمال طول الطابور و اكتشاف الأجسام
Dissertant
al-Ayish, Ubadah Muhammad Adnan
Thesis advisor
Comitee Members
al-Smadi, Adnan M.
Slait, Azzam Talal
Hamarishah, Akram
University
Al albayt University
Faculty
Prince Hussein Bin Abdullah Faculty for Information Technology
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2010
English Abstract
As the social economic activities grow variously in recent days, an advanced traffic control system corresponding to the changes of road traffic circumstances becomes an urgent matter.
This research suggests two techniques based on picture taken by digital camera placed at fixed position in the traffic light with specific resolution and distance.
The resulted image will be preprocessed (subtract image from its background, remove noisy small objects) then use two techniques queue length (find out the length of car queue on road depending on the distance between the two end points on road line), and vehicle counting (by performing image segmentation and count out segments that satisfy the proper size of vehicle).To measure the queue length or to count the number of the vehicles, edge detection (in this research Sobol edge detection method is used) and segmentation (based on region growing) are needed.
Finally, an equation to find out the estimated time and actual time is suggested to determine the estimated time reference for optic Green.
The two suggested techniques compared from two points of views: time needed to make decision of green-light period, and the suggested estimated time by the technique with respect to the actual time needed.
As a result, it was found the vehicle counting technique is recommended to be used since it shows better performance from decision making time and estimated time with respect to actual.
Also the Impact of image quality (low and high density of vehicles on road) is studied, where it was found that the queue suit high density road vehicle counting suit low density road, but generally segmentation suitable for both types.
Main Subjects
Information Technology and Computer Science
Topics
No. of Pages
63
Table of Contents
Table of contents.
Abstract.
Chapter One : introduction.
Chapter Two : main principles of image processing.
Chapter Three : system development.
Chapter Four : experimental results.
Chapter Five : conclusions and future works.
References.
American Psychological Association (APA)
al-Ayish, Ubadah Muhammad Adnan. (2010). Traffic light control utilizing queue length and object segmentation. (Master's theses Theses and Dissertations Master). Al albayt University, Jordan
https://search.emarefa.net/detail/BIM-314908
Modern Language Association (MLA)
al-Ayish, Ubadah Muhammad Adnan. Traffic light control utilizing queue length and object segmentation. (Master's theses Theses and Dissertations Master). Al albayt University. (2010).
https://search.emarefa.net/detail/BIM-314908
American Medical Association (AMA)
al-Ayish, Ubadah Muhammad Adnan. (2010). Traffic light control utilizing queue length and object segmentation. (Master's theses Theses and Dissertations Master). Al albayt University, Jordan
https://search.emarefa.net/detail/BIM-314908
Language
English
Data Type
Arab Theses
Record ID
BIM-314908
