Vision-based system for qualitative road traffic data analysis

According to the UK National Transport Ministry, road traffic was projected to increase by 44% more, compared with the Figure in 2011, by the year of 2035. As the pace of the modrn life escalated the demand of transport needed to be dealt with. Currently, surveillance cameras were the most common de...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Zhang, Chenyu
مؤلفون آخرون: Mohammed Yakoob Siyal
التنسيق: Final Year Project
اللغة:English
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10356/53077
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
id sg-ntu-dr.10356-53077
record_format dspace
spelling sg-ntu-dr.10356-530772023-07-07T16:14:23Z Vision-based system for qualitative road traffic data analysis Zhang, Chenyu Mohammed Yakoob Siyal School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision According to the UK National Transport Ministry, road traffic was projected to increase by 44% more, compared with the Figure in 2011, by the year of 2035. As the pace of the modrn life escalated the demand of transport needed to be dealt with. Currently, surveillance cameras were the most common devices deployed to monitor road traffic. Statistics would be gathered for post investigation. However, the process involves ineffective manual counting. With the help of vision-based traffic supervision tool more precise road traffic information can be provided in time for speculation.The project was aimed to improve the quality of the traffic supervision software. Therefore various enhancing techniques were compared and contrasted. MATLAB was used to build the GUI and run the programs to achieve functions designated to traffic analysis. Results obtained were analysed in parallel with one another to determine the superiority. Real time image acquisition, dynamic background extraction, shadow and highlight detection by calculating the distortion, image reconstruction and fuzzy logic classification were applied to achieve a better result. The software was enabled to apply to more practical situations where various weather conditions occur, traffic be congested or other traffic abnormalities. Bachelor of Engineering 2013-05-29T09:12:34Z 2013-05-29T09:12:34Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53077 en Nanyang Technological University 54 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Zhang, Chenyu
Vision-based system for qualitative road traffic data analysis
description According to the UK National Transport Ministry, road traffic was projected to increase by 44% more, compared with the Figure in 2011, by the year of 2035. As the pace of the modrn life escalated the demand of transport needed to be dealt with. Currently, surveillance cameras were the most common devices deployed to monitor road traffic. Statistics would be gathered for post investigation. However, the process involves ineffective manual counting. With the help of vision-based traffic supervision tool more precise road traffic information can be provided in time for speculation.The project was aimed to improve the quality of the traffic supervision software. Therefore various enhancing techniques were compared and contrasted. MATLAB was used to build the GUI and run the programs to achieve functions designated to traffic analysis. Results obtained were analysed in parallel with one another to determine the superiority. Real time image acquisition, dynamic background extraction, shadow and highlight detection by calculating the distortion, image reconstruction and fuzzy logic classification were applied to achieve a better result. The software was enabled to apply to more practical situations where various weather conditions occur, traffic be congested or other traffic abnormalities.
author2 Mohammed Yakoob Siyal
author_facet Mohammed Yakoob Siyal
Zhang, Chenyu
format Final Year Project
author Zhang, Chenyu
author_sort Zhang, Chenyu
title Vision-based system for qualitative road traffic data analysis
title_short Vision-based system for qualitative road traffic data analysis
title_full Vision-based system for qualitative road traffic data analysis
title_fullStr Vision-based system for qualitative road traffic data analysis
title_full_unstemmed Vision-based system for qualitative road traffic data analysis
title_sort vision-based system for qualitative road traffic data analysis
publishDate 2013
url http://hdl.handle.net/10356/53077
_version_ 1772828356227629056