• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4419-4441
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• 2016

A cause of vehicle accidents is the reduced visibility due to bad weather conditions such as fog. Therefore, an onboard vision system should take visibility detection into account. In this paper, we propose a simple and effective approach for measuring the visibility distance using a single camera placed onboard a moving vehicle. The proposed algorithm is controlled by a few parameters and mainly includes camera parameter estimation, region of interest (ROI) estimation and visibility computation. Thanks to the ROI extraction, the position of the inflection point may be measured in practice. Thus, combined with the estimated camera parameters, the visibility distance of the input foggy image can be computed with a single camera and just the presence of road and sky in the scene. To assess the accuracy of the proposed approach, a reference target based visibility detection method is also introduced. The comparative study and quantitative evaluation show that the proposed method can obtain good visibility detection results with relatively fast speed.

• Textile Coloration and Finishing
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• v.33 no.4
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• pp.288-301
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• 2021

The purpose of this study was to verify the degree of visibility of FOLED (fiber optic light-emitting diode) materials applied to safety-enhancing clothes of micro-mobility users during the day and night by conducting an empirical test targeting 50 people in their teens, 20's, 30's, 40's, and 50's or older. First, the results of the visibility test at 10 m-intervals from 10 to 70 m based on the clothes sample showed that the light detection of FOLED material was very good without daytime or night-time distinction. Second, the results of directional sign detection of FOLED were confirmed to be very high without any daytime or night. Third, the results of identifying a pictogram design showed that the distance was shorter than that of light detection or directional indication. However, the FOLED pictogram design could be confirmed at a distance of 50 m or less. Therefore, if a clothes product using FOLED material is worn and micro-mobility is used, the experimental results indicate that safety will be sufficiently secured due to the excellent visibility.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.137-148
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• 2017

The present study examined the effect of stimulus contrast and color on detection of a target embedded in streams of letters. In Experiment 1, each trial displayed four rapid serial visual presentation (RSVP) streams of letters (i.e., multi-RSVP), and each stream occupied one of four different locations. Each frame in the RSVP stream had four white distractors at the locations except one frame where a dim grey target was displayed at a location with three white distractors at the remaining locations. In the low-visibility target condition, the target's grey color was slightly darker than the background grey whereas much dimmer in the high-visibility condition. Participants were asked to report presence of a predesignated target as quickly and accurately as possible upon its detection in each trial, and their target detection turned out more accurate and quicker in the high-visibility than the low-visibility condition. In Experiment 2, the same RSVP displays and task as Experiment were used, but the grey target letters in the high-visibility condition were replaced with those of distinct chromatic colors. Participants detected target presence more accurately in the high-visibility condition, but the reaction time did not differ between the visibility conditions. The results indicate that higher stimulus contrast as well as distinct color can improve perception of a target stimulus displayed among visually-demanding background, but also suggest that stimulus contrast may play a more substantial role for such perceptual improvement.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.117-136
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• 2019

In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.391-395
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• 2023

Helicopter accidents due to spatial disorientation in low visibility conditions continue to persist as a major issue. These incidents often stem from human error, typically induced by stress, and frequently result in fatal outcomes. This study employs machine learning to analyze flight data and evaluate the efficacy of a flight illusion detection algorithm, laying groundwork for further research. This study collected flight data from approximately 20 pilots using a simulated flight training device to construct a range of flight scenarios. These scenarios included three stages of flight: ascending, level, and descent, and were further categorized into good visibility conditions and 0-mile visibility conditions. The aim was to investigate the occurrence of flight illusions under these conditions. From the extracted data, we obtained a total of 54,000 time-series data points, sampled five times per second. These were then analyzed using a machine learning approach.

• Journal of Sensor Science and Technology
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• v.23 no.3
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• pp.149-157
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• 2014

This paper considers the ability of counting and positioning multi-targets by using a mobile UWB radar device. After a background subtraction process, distinguishing between clutters and human body signals, the position of targets will be computed using weighted Gaussian mixture methods. While computer vision offers many advantages, it has limited performance in poor visibility conditions (e.g., at night, haze, fog or smoke). UWB radar can provide a complementary technology for detecting and tracking humans, particularly in poor visibility or through-wall conditions. As we know, for 2D measurement, one method is the use of at least two receiver antennas. Another method is the use of one mobile radar receiver. This paper tried to investigate the position detection of the stationary human body using the movement of one UWB radar module.

• Smart Media Journal
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• v.12 no.10
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• pp.19-28
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• 2023

In the fruit harvesting field, interest in automatic robot harvesting is increasing due to various seasonality and rising harvesting costs. Accurate apple detection is a difficult problem in complex orchard environments with changes in light, vibrations caused by wind, and occlusion of leaves and branches. In this paper, we introduce a dataset and an adaptive heatmap regression model that are advantageous for robot automatic apple harvesting. The apple dataset was labeled with not only the apple location but also the visibility. We propose a method to detect the center point of an apple using an adaptive heatmap regression model that adjusts the Gaussian shape according to visibility. The experimental results showed that the performance of the proposed method was applicable to apple harvesting robots, with MAP@K of 0.9809 and 0.9801 when K=5 and K=10, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.101-115
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• 2022

This study compared the performance of LiDAR in detecting objects in rough weather with that in clear weather. An experiment that reproduced rough weather divided the fog visibility into four stages from 200 m to 50 m and controlled the rainfall by dividing it into 20 mm/h and 50 mm/h. The number of points cloud and intensity were used as the performance indicators. The difference in performance was statistically investigated by a T-Test. The result of the study indicates that the performance of LiDAR decreased in the order in situations of 20 mm/h rainfall, fog visibility less than 200 m, 50 mm/h rainfall, fog visibility less than 150 m, fog visibility less than 100 m, and fog visibility less than 50 m. The decreased performance was greater when the measurement distance was greater and when the color was black rather than white. However, in the case of white, there was no difference in performance at a measurement distance of 10 m even at 50 m fog visibility, which is considered the worst situation in this experiment. This no difference in performance was also statistically significant. These performance verification results are expected to be utilized in the manufacture of road facilities in the future that improve the visibility of sensors.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.9-16
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• 2012

The performance of road markings is classified into the visibility at daytime, night time, wet condition and rainy conditions. The objective of this study is to obtain the driving safety of drivers under conditions of unstable weather condition such as the rain. The visibility of road markings is closely related to the preview time and detection distances and the ways to improve road marking materials and increase the dry retroreflectivity and wet retroreflectivity, which are the measures of daytime and nighttime visibility is researched to decrease the traffic accidents. For this purpose, Road marking glass beads with the refraction rate of 1.5 and 2.2 are introduced to raise the retroreflectivity. After investigating the minimum threshold retroreflectivity and Install Minimum retroreflectivity at home and abroad, minimum control values for the roadmarking visibility and improvement of nightime rainy retroreflectivity are suggested by physical properties and retroreflectivity experiments.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.441-451
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• 2014

This study proposes a novel performance measure, which is referred to as Hazardous Spacing Index (HSI), to be used for evaluating safety of traffic stream on freeways. The basic principle of the proposed methodology is to investigate whether drivers would have sufficient stopping sight distance (SSD) under limited visibility conditions to eliminate rear-end crash potentials at every time step. Both Road Weather Information Systems (RWIS) and Vehicle Detection Systems (VDS) data were used to derive visibility distance (VD) and SSD, respectively. Moreover, the K-Nearest Neighbors (KNN) method was adopted to predict both VD and SSD in estimating predictive HSIs, which would be used to trigger advanced warning information to encourage safer driving. The outcome of this study is also expected to be used for monitoring freeway traffic stream in terms of safety.