scholarly journals A Vehicle Speed Measurement System For Nighttime with Camera

2014 ◽  
Author(s):  
Yujie Goda ◽  
Lifeng Zhang ◽  
Seiichi Serikawa
Keyword(s):  
Measurement System ◽  
Vehicle Speed ◽  
Speed Measurement

scholarly journals An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 866
Author(s):  
Lei Yang ◽  
Qingyuan Li ◽  
Xiaowei Song ◽  
Wenjing Cai ◽  
Chunping Hou ◽  
...  
Keyword(s):  
Image Fusion ◽  
Measurement System ◽  
Stereo Matching ◽  
License Plate ◽  
Vehicle Speed ◽  
Matching Algorithm ◽  
Speed Measurement ◽  
Optimum Speed ◽  
Binocular Stereo ◽  
Plate Area

This paper proposes an improved stereo matching algorithm for vehicle speed measurement system based on spatial and temporal image fusion (STIF). Firstly, the matching point pairs in the license plate area with obviously abnormal distance to the camera are roughly removed according to the characteristic of license plate specification. Secondly, more mismatching point pairs are finely removed according to local neighborhood consistency constraint (LNCC). Thirdly, the optimum speed measurement point pairs are selected for successive stereo frame pairs by STIF of binocular stereo video, so that the 3D points corresponding to the matching point pairs for speed measurement in the successive stereo frame pairs are in the same position on the real vehicle, which can significantly improve the vehicle speed measurement accuracy. LNCC and STIF can be used not only for license plate, but also for vehicle logo, light, mirror etc. Experimental results demonstrate that the vehicle speed measurement system with the proposed LNCC+STIF stereo matching algorithm can significantly outperform the state-of-the-art system in accuracy.

An FPGA-based vehicle speed measurement system using an uncalibrated camera

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Ji Ho Song ◽  
Nguyen Tuong Thuy ◽  
Seunghun Jin ◽  
Dongkyun Kim ◽  
Jae Wook Jeon
Keyword(s):  
Measurement System ◽  
Vehicle Speed ◽  
Uncalibrated Camera ◽  
Speed Measurement

scholarly journals Robust Vehicle Speed Measurement Based on Feature Information Fusion for Vehicle Multi-Characteristic Detection

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 910
Author(s):  
Lei Yang ◽  
Jianchen Luo ◽  
Xiaowei Song ◽  
Menglong Li ◽  
Pengwei Wen ◽  
...  
Keyword(s):  
Measurement Error ◽  
Object Detection ◽  
Information Fusion ◽  
Measurement System ◽  
Error Rate ◽  
Detection Algorithm ◽  
Vehicle Speed ◽  
Channel Interaction ◽  
Speed Measurement ◽  
Feature Information

A robust vehicle speed measurement system based on feature information fusion for vehicle multi-characteristic detection is proposed in this paper. A vehicle multi-characteristic dataset is constructed. With this dataset, seven CNN-based modern object detection algorithms are trained for vehicle multi-characteristic detection. The FPN-based YOLOv4 is selected as the best vehicle multi-characteristic detection algorithm, which applies feature information fusion of different scales with both rich high-level semantic information and detailed low-level location information. The YOLOv4 algorithm is improved by combing with the attention mechanism, in which the residual module in YOLOv4 is replaced by the ECA channel attention module with cross channel interaction. An improved ECA-YOLOv4 object detection algorithm based on both feature information fusion and cross channel interaction is proposed, which improves the performance of YOLOv4 for vehicle multi-characteristic detection and reduces the model parameter size and FLOPs as well. A multi-characteristic fused speed measurement system based on license plate, logo, and light is designed accordingly. The system performance is verified by experiments. The experimental results show that the speed measurement error rate of the proposed system meets the requirement of the China national standard GB/T 21555-2007 in which the speed measurement error rate should be less than 6%. The proposed system can efficiently enhance the vehicle speed measurement accuracy and effectively improve the vehicle speed measurement robustness.

Compensating Background for Noise due to Camera Vibration in Uncalibrated-Camera-Based Vehicle Speed Measurement System

2011 ◽  
Vol 60 (1) ◽  
pp. 30-43 ◽  
Author(s):  
Thuy Tuong Nguyen ◽  
Xuan Dai Pham ◽  
Ji Ho Song ◽  
Seunghun Jin ◽  
Dongkyun Kim ◽  
...  
Keyword(s):  
Measurement System ◽  
Vehicle Speed ◽  
Uncalibrated Camera ◽  
Speed Measurement

scholarly journals Parallel Implementation of a Video-based Vehicle Speed Measurement System for Municipal Roadways

2019 ◽  
Vol 11 (11) ◽  
pp. 25-37
Author(s):  
Abdorreza Joe Afshany ◽  
◽  
Ali Tourani ◽  
Asadollah Shahbahrami ◽  
Saeed Khazaee ◽  
...  
Keyword(s):  
Measurement System ◽  
Parallel Implementation ◽  
Vehicle Speed ◽  
Speed Measurement

Color image analysis for vehicle speed measurement

1993 ◽  
Vol 20 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Yean-Jye Lu ◽  
Xidong Yuan
Keyword(s):  
Image Analysis ◽  
Traffic Control ◽  
Road Traffic ◽  
Color Image ◽  
Image Data ◽  
Difficult Problem ◽  
Vehicle Speed ◽  
Color Image Analysis ◽  
Speed Measurement ◽  
Monochrome Image

Image analysis for traffic data collection has been studied throughout the world for more than a decade. A survey of existing systems shows that research was focused mainly on the monochrome image analysis and that the field of color image analysis was rarely studied. With the application of color image analysis in mind, this paper proposes a new algorithm for vehicle speed measurement in daytime. The new algorithm consists of four steps: (i) image input, (ii) pixel analysis, (iii) single image analysis, and (iv) image sequence analysis. It has three significant advantages. First, the algorithm can distinguish the shadows caused by moving vehicles outside the detection area from the actual vehicles passing through the area, which is a difficult problem for the monochrome image analysis technique to handle. Second, the algorithm significantly reduces the image data to be processed; thus only a personal computer is required without the addition of any special hardware. The third advantage is the flexible placement of detection spots at any position in the camera's field of view. The accuracy of the algorithm is also discussed. Key words: speed measurement, vehicle detection, image analysis, image processing, traffic control, traffic measurement and road traffic.

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