Analysis of the Influence of Foggy Weather Environment on the Detection Effect of Machine Vision Obstacles

Liu, Zhaohui; He, Yongjiang; Wang, Chao; Song, Runze

doi:10.3390/s20020349

Cited by 38 publications

(31 citation statements)

References 19 publications

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“…As autonomous navigation technology for self-driving cars, drones, and airplanes is required, research to recognize people or objects in fog has been extensively conducted [ 4 , 5 , 6 , 7 ]. These studies are based on existing computer vision and image processing algorithms, but they show unlimited possibilities for autonomous navigation by using AI as a new tool.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Safety-Related Sensors in Low Visibility by Fog

Kim

Sumi

2020

Sensors

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Mobile service robots are expanding their use to outdoor areas affected by various weather conditions, but the outdoor environment directly affects the functional safety of robots implemented by vision-based safety-related sensors (SRSs). Therefore, this paper aims to set the fog as the environmental condition of the robot and to understand the relationship between the quantified value of the environmental conditions and the functional safety performance of the robot. To this end, the safety functions of the robot built using SRS and the requirements for the outdoor environment affecting them are described first. The method of controlling visibility for evaluating the safety function of SRS is described through the measurement and control of visibility, a quantitative means of expressing the concentration of fog, and wavelength analysis of various SRS light sources. Finally, object recognition experiments using vision-based SRS for robots are conducted at low visibility. Through this, it is verified that the proposed method is a specific and effective method for verifying the functional safety of the robot using the vision-based SRS, for low visibility environmental requirements.

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Section: Introductionmentioning

confidence: 99%

Vision-Based Safety-Related Sensors in Low Visibility by Fog

Kim

Sumi

2020

Sensors

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“…Fog is also an adverse weather condition that can occur in the driving environment. The object detection performance of Faster R-CNN [122] in four levels of foggy weather: clear (no fog), light, medium, heavy is analysed in [159]. Other works could be found in [160]- [162].…”

Section: ) Self-driving Scenariosmentioning

confidence: 99%

Toward Performing Image Classification and Object Detection With Convolutional Neural Networks in Autonomous Driving Systems: A Survey

Turay

Vladimirova

2022

IEEE Access

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“…The paper [ 101 ] presented a study on how a foggy weather environment can influence the accuracy of machine vision obstacle detection in the context of assisted driving. A foggy day imaging model is described, and the image characteristics are analyzed.…”

Section: Sensors and Systems For Fog Detection And Visibility Enhancementmentioning

confidence: 99%

Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems

Miclea

Ungureanu

Sandru

et al. 2021

Sensors

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In mobile systems, fog, rain, snow, haze, and sun glare are natural phenomena that can be very dangerous for drivers. In addition to the visibility problem, the driver must face also the choice of speed while driving. The main effects of fog are a decrease in contrast and a fade of color. Rain and snow cause also high perturbation for the driver while glare caused by the sun or by other traffic participants can be very dangerous even for a short period. In the field of autonomous vehicles, visibility is of the utmost importance. To solve this problem, different researchers have approached and offered varied solutions and methods. It is useful to focus on what has been presented in the scientific literature over the past ten years relative to these concerns. This synthesis and technological evolution in the field of sensors, in the field of communications, in data processing, can be the basis of new possibilities for approaching the problems. This paper summarizes the methods and systems found and considered relevant, which estimate or even improve visibility in adverse weather conditions. Searching in the scientific literature, in the last few years, for the preoccupations of the researchers for avoiding the problems of the mobile systems caused by the environmental factors, we found that the fog phenomenon is the most dangerous. Our focus is on the fog phenomenon, and here, we present published research about methods based on image processing, optical power measurement, systems of sensors, etc.

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Analysis of the Influence of Foggy Weather Environment on the Detection Effect of Machine Vision Obstacles

Cited by 38 publications

References 19 publications

Vision-Based Safety-Related Sensors in Low Visibility by Fog

Vision-Based Safety-Related Sensors in Low Visibility by Fog

Toward Performing Image Classification and Object Detection With Convolutional Neural Networks in Autonomous Driving Systems: A Survey

Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems

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