Iccsa Geog An Mod Elke Moons

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Third International Workshop on "Geographical Analysis, Urban Modeling, Spatial Statistics"

Business Technology

Hot Spot Analysis: Improving a LISA for application in traffic safety Elke Moons Transportation Research Institute (IMOB) Hasselt University Belgium E-mail: elke.moons@uhasselt.be ICCSA Conference Geog-An-Mod workshop

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The goal of Red Light Violation Detection System RLVDS is to track down vehicles that violated traffic regulations using surveillance cameras and image processing techniques. A complete automated red light runner detection algorithm that satisfies real time requirement and gives higher accuracy have been developed. The system detects simultaneously a traffic light sequence, stop line and detection region to detect moving vehicles and capture the vehicles beyond the stop line while the light is red and finally generates the red light running vehicle images with date and time information. In this paper, we propose a traffic light detection algorithm which is one of the processes of automated red light runner detection system. The proposed traffic light detection system includes four steps color space conversion based on RGB color space, some regions are extracted as candidates of a traffic light and morphological operation is applied to eliminate disturbance in the environment that can interfere with the traffic light states. Then, the types of traffic signals are judged by calculating image moments and the results of experiment show that the system is stable and reliable. Thwe War War Zaw | Ohnmar Win ""Traffic Light Detection for Red Light Violation System"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25185.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25185/traffic-light-detection-for-red-light-violation-system/thwe-war-war-zaw

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In this paper, variability analysis was performed o n the model calibration methodology between a multi-camera system and a LiDAR laser sensor (Lig ht Detection and Ranging). Both sensors are used to digitize urban environments. A practica l and complete methodology is presented to predict the error propagation inside the LiDAR-came ra calibration. We perform a sensitivity analysis in a local and global way. The local appro ach analyses the output variance with respect to the input, only one parameter is varied at once. In the global sensitivity approach, all parameters are varied simultaneously and sensitivit y indexes are calculated on the total variation range of the input parameters. We quantif y the uncertainty behaviour in the intrinsic camera parameters and the relationship between the noisy data of both sensors and their calibration. We calculated the sensitivity indexes by two techniques, Sobol and FAST (Fourier amplitude sensitivity test). Statistics of the sens itivity analysis are displayed for each sensor, the sensitivity ratio in laser-camera calibration data

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