Monitoring System for Overspeeding Vehicles Using Computer Vision Technology /
Villanueva, Jan Ross A., author.
Monitoring System for Overspeeding Vehicles Using Computer Vision Technology / Jan Ross A. Villanueva and Margie M. Presidente. - Rosario, Cavite : Cavite State University-CCAT Campus, 2018 - xii, 56 leaves : illustrations ; 28 cm
Design Project (BSCpE)--Cavite State University-CCAT Campus, 2018.
Includes bibliographical references and appendices.
VILLANUEVA JAN ROSS A., PRESIDENTE MARGIE M. Monitoring System for Overspeeding Vehicles Using Computer Vision Technology. Design Project. Department of Engineering. Cavite State University-CCAT Campus, Rosario, Cavite. June 2018. Adviser: Mr. Karlo Jose E. Nabablit. Technical critic: Allen Paul K. Aclan.
The study was conducted from November 2017 until May 2018 to develop a monitoring system for the overspeeding vehicles using computer vision. Specifically, the study aimed to; 1.) design the graphical user interface and physical design of the system; 2.) construct the software and hardware requirements of the speed monitoring system by creating the graphical and logical interface of the system using Tkinter platform in Python; and 3.test the accuracy of computer vision system using t-test method.
In developing the research topic, the developers used a research design which includes initial research and study, planning and initial designing, extensive research for algorithms and functions, assembly and installation, creating of source code, acquiring required materials, testing, debugging and evaluation.
The monitoring system was evaluated by identifying if there is a significant difference between the manual readings of the speedometer and the actual reading of the system. Ten samples were gathered and analysed through T-test method. The researchers got a p-value of 0.101475, indicating that there is no significant difference between the readings of speedometer and the system. This implies that the developed system provides an accurate readings.
Computer vision.
Automated traffic monitoring system.
Speed estimation.
Video signal processing.
UM TL 272.53 / V55 2018
Monitoring System for Overspeeding Vehicles Using Computer Vision Technology / Jan Ross A. Villanueva and Margie M. Presidente. - Rosario, Cavite : Cavite State University-CCAT Campus, 2018 - xii, 56 leaves : illustrations ; 28 cm
Design Project (BSCpE)--Cavite State University-CCAT Campus, 2018.
Includes bibliographical references and appendices.
VILLANUEVA JAN ROSS A., PRESIDENTE MARGIE M. Monitoring System for Overspeeding Vehicles Using Computer Vision Technology. Design Project. Department of Engineering. Cavite State University-CCAT Campus, Rosario, Cavite. June 2018. Adviser: Mr. Karlo Jose E. Nabablit. Technical critic: Allen Paul K. Aclan.
The study was conducted from November 2017 until May 2018 to develop a monitoring system for the overspeeding vehicles using computer vision. Specifically, the study aimed to; 1.) design the graphical user interface and physical design of the system; 2.) construct the software and hardware requirements of the speed monitoring system by creating the graphical and logical interface of the system using Tkinter platform in Python; and 3.test the accuracy of computer vision system using t-test method.
In developing the research topic, the developers used a research design which includes initial research and study, planning and initial designing, extensive research for algorithms and functions, assembly and installation, creating of source code, acquiring required materials, testing, debugging and evaluation.
The monitoring system was evaluated by identifying if there is a significant difference between the manual readings of the speedometer and the actual reading of the system. Ten samples were gathered and analysed through T-test method. The researchers got a p-value of 0.101475, indicating that there is no significant difference between the readings of speedometer and the system. This implies that the developed system provides an accurate readings.
Computer vision.
Automated traffic monitoring system.
Speed estimation.
Video signal processing.
UM TL 272.53 / V55 2018