• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.108-115
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• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.385-392
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• 2013

A key element of the fog warning system to prevent large traffic accidents is a visibility measurement device. Recently, the need for it that is similar to the human visual sense and cheap and accurate than expensive fog sensors is increasing. In this paper, we present the performance evaluation and the economic analysis of the Road Visibility Measurement System (RVMS), which is developed for measuring the road visibility through a CCTV camera. For experiments, we have installed a CCTV camera, a fog sensor, and visibility signs at the Yeo-ju Test Road on the Central Inland Expressway. We evaluated the measurements from RVMS and the fog sensor based on observations. The result shows RVMS outperforms the fog sensor with respect to measurement stability and correctness. We also show RVMS has higher economic feasibility and various applications. RVMS can prevent the traffic accidents caused by severe fog and enhance the process of the wide-area visibility information system significantly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• Journal of Environmental Science International
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• v.9 no.5
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• pp.385-388
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• 2000

Visibility reduction is a barometer of air pollution which people can notice easily. First of all we need to measure quantified visibility continuously in order to examine visibility reduction. Prevailing visibility is not practical to measure visibility depending on observer's expertness. Scattering visibility using Forward Scattering Meter(Belfort Visibility Sensor 6230) has been measured at Kwangan-Dong in Pusan and analysed since July 1998. According to the analysis the correlation coefficient(R) between prevailing visibility and scattering visibility was 0.7235. The visibility appeared that each frequency of poor visibility(under 6km) and good visibility(over 25km) was 10.6%, 9.7% on summertime in Pusan and the visibility range from 10km to 20km ranked high frequency as a half of whole ranges. The order of correlation coefficients between visibility an air pollutants are ranking CO. PM10 and NO2 that values are 0.5878, 0.5369,l 0.5284 respectively. In meteorolgical factor the case of poor visibility presented more weakly wind speed and higher relative humidity than the case of good visibility. The correlation coefficient between calculated visibility of multiple linear regression model and observed visibility was 0.7215. But the trend of calculated and observed visibility variation was similar with the exception of several good visibility cases.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.92-99
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• 2002

To obtain visual information of a target object, a camera should be placed within the visibility region. As the visibility region is dependent on the relative position of the target object and the surrounding object, the position change of the surrounding object during a task requires recalculation of the visibility region. For a fast computation of the visibility region so as to modify the camera position to be located within the visibility region, we propose a spherical projection method. After being projected onto the sphere the visibility region is represented in $\theta$-$\psi$ spaces of the spherical coordinates. The reduction of calculation space enables a fast modification of the camera location according to the motion of the surrounding objects so that the continuous observation of the target object during the task is possible.

• Atmosphere
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• v.29 no.4
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• pp.439-450
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• 2019

Present weather plays an important role not only for atmospheric sciences but also for public welfare and road safety. While the widely used state-of-the-art visibility and present weather sensor yields present weather, a single type of measurement is far from perfect to replace long history of human-eye based observation. Truly automatic present weather observation enables us to increase spatial resolution by an order of magnitude with existing facilities in Korea. 8 years of human-eyed present weather records in 19 sites over Korea are compared with visibility sensors and auxiliary measurements, such as humidity of AWS. As clear condition agrees with high probability, next best categories follow fog, rain, snow, mist, haze and drizzle in comparison with human-eyed observation. Fog, mist and haze are often confused due to nature of machine sensing visibility. Such ambiguous weather conditions are improved with empirically induced criteria in combination with visibility and humidity. Differences between instrument manufacturers are also found indicating nonstandard present weather decision. Analysis shows manufacturer dependent present weather differences are induced by manufacturer's own algorithms, not by visibility measurement. Accuracies of present weather for haze, mist, and fog are all improved by 61.5%, 44.9%, and 26.9% respectively. The result shows that automatic present weather sensing is feasible for operational purpose with minimal human interactions if appropriate algorithm is applied. Further study is ongoing for impact of different sensing types between manufacturers for both visibility and present weather data.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.311-321
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• 2007

The diffuse attenuation coefficient for down-welling irradiance $K_d({\lambda})$, which is the propagation of down-welling irradiance at wavelength ${\lambda}$ from surface to a depth (z) in the ocean, and underwater visibility are important optical parameters for ocean studies. There have been several studies on $K_d({\lambda})$ and underwater visibility around the world, but only a few studies have focused on these properties in the Korean sea. Therefore, in the present study, we studied $K_d({\lambda})$ and underwater visibility around the coastal area of the Yellow Sea, and developed $K_d({\lambda})$ and underwater visibility algorithms for ocean color satellite sensor. For this research we conducted a field campaign around the Yellow Sea from $19{\sim}22$ September, 2006 and there we obtained a set of ocean optical and environmental data. From these datasets the $K_d({\lambda})$ and underwater visibility algorithms were empirically derived and compared with the existing NASA SeaWiFS $K_d({\lambda})$ algorithm and NRL (Naval Research Laboratory) underwater visibility algorithm. Such comparisons over a turbid area showed small difference in the $K_d({\lambda})$ algorithm and constants of our result for underwater visibility algorithm showed slightly higher values.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.65-73
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• 2010

To observe and analyze the characteristics of cloud and precipitation properties, the Cloud physics Observation System (CPOS) has been operated from December 2003 at Daegwallyeong ($37.4^{\circ}N$, $128.4^{\circ}E$, 842 m) in the Taebaek Mountains. The major instruments of CPOS are follows: Forward Scattering Spectrometer Probe (FSSP), Optical Particle Counter (OPC), Visibility Sensor (VS), PARSIVEL disdrometer, Microwave Radiometer (MWR), and Micro Rain Radar (MRR). The former four instruments (FSSP, OPC, visibility sensor, and PARSIVEL) are for the observation and analysis of characteristics of the ground cloud (fog) and precipitation, and the others are for the vertical cloud characteristics (http://weamod.metri.re.kr) in real time. For verification of CPOS products, the comparison between the instrumental products has been conducted: the qualitative size distributions of FSSP and OPC during the hygroscopic seeding experiments, the precipitable water vapors of MWR and radiosonde, and the rainfall rates of the PARSIVEL(or MRR) and rain gauge. Most of comparisons show a good agreement with the correlation coefficient more than 0.7. These reliable CPOS products will be useful for the cloud-related studies such as the cloud-aerosol indirect effect or cloud seeding. The visibility value is derived from the droplet size distribution of FSSP. The derived FSSP visibility shows the constant overestimation by 1.7 to 1.9 times compared with the values of two visibility sensors (SVS (Sentry Visibility Sensor) and PWD22 (Present Weather Detect 22)). We believe this bias is come from the limitation of the droplet size range ($2{\sim}47\;{\mu}m$) measured by FSSP. Further studies are needed after introducing new instruments with other ranges.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.6
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• pp.665-671
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• 2014

Recent researches show that the traffic fatality rate in fog is higher than that in rain and snow. In that sense, methods to measure visibility accurately and to notify the measured visibility information to drivers are required. We thus developed a system for measuring the road visibility in realtime by employing CCTV cameras. In this paper, we also propose a wide-area visibility information system through measuring the visibility of every highway by using the developed system. The proposed wide-area visibility information system uses the video clips from the CCTV camera instead of the output from the expensive fog sensor. Hence, we expect that it can reduce the cost of installation and operation dramatically and the measured visibility information has a number of applications.

• Imaging Science in Dentistry
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• v.34 no.3
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• pp.145-150
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• 2004

Purpose: To compare three digital radiographic imaging sensors by evaluating the visibility of endodontic file tips with interobserver reproducibility and assessing subjectively the clarity of images in comparison with the x-ray film images. Materials and Methods: Forty-five extracted sound premolars were used for this study. Fifteen plaster blocks were made with three premolars each and #8, 10, 15 K-flexofiles were inserted into the root canal of premolars. They were radiographically exposed using periapical x-ray films (Kodak Insight Dental film, Eastmann Kodak company, Rochester, USA), Digora imaging plates (Soredex-Orion Co., Helsinki, Finland), CDX 2000HQ sensors (Biomedisys Co., Seoul, Korea), and CDR sensors (Schick Inc., Long Island, USA). The visibility of endodontic files was evaluated with interobserver reproducibility, which was calculated as the standard deviations of X, Y coordinates of endodontic file tips measured on digital images by three oral and maxillofacial radiologists. The clarity of images was assessed subjectively using 3 grades, i.e. plus, equal, and minus in comparison with the conventional x-ray film images. Results: Interobserver reproducibility of endodontic file tips was the highest in CDR sensor (p < 0.05) only except at Y coordinates of #15 file. In the subjective assessment of the image clarity, the plus grade was the most frequent in CDR sensor at all size of endodontic file (p < 0.05). Conclusion : CDR sensor was the most superior to the other sensors, CDX 2000HQ sensor and Digora imaging plate in the evaluation of interobserver reproducibility of endodontic file tip and subjective assessment of image clarity.