• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.11-19
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• 2016

Recently, global companies are developing the automobile technologies, converged with state-of-the-art IT technologies for the commercialization of autonomous vehicles. These autonomous vehicles are required the accurate lane information to enhance its reliability by controlling the vehicles safely. Hence, the study planned to examine possibilities of applying UAV photogrammetry of high-resolution images, obtained from the low altitudes. The high-resolution DSM and the ortho-images were generated from the GSD 7cm-level digital images that were obtained and based on the generated data, when the positions information of the roads including the lanes were extracted. In fact, the RMSE of verifying the extracted data was shown to be about 15cm. Through the results from the study, it could be concluded that the low alititude UAV photogrammetry can be applied for generating and updating a high-accuracy map of road areas.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.85-94
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• 2012

Lane marking detection is essential to both ITS and DAS systems. The objective of this paper is to provide more robust technique for lane marking detection than traditional techniques by using scale-space technique. Variable thresholding that is based on the local statistics may be very effective for detecting such objects as lane markings that have prominent intensities. However, such techniques that only rely on local statistics have limitations containing irrelevant areas as well. We reduce the candidate areas by combining the variable thresholding result with cost-efficient horizontal 1D LoG filtered scale space. Through experiments using practical images, we could achieve significant improvement over the techniques based not only on the variable thresholding but also on the Hough transform that is another very popular technique for this purpose.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1327-1335
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• 2012

TPMS (Tire Pressure Monitoring System) is a safety assistant system to prevent the serious accident due to the damaged tire by the abnormal tire pressure. It is designed to transmit the measured data for pressure and temperature of tires from the sensor unit installed in each tire to signal processing unit installed in a vehicle. Based on the received information, a driver monitors the condition of tires using a display device, to maintain the optimum travelling condition. Since TPMS should employ the wireless communication technique, it may suffer from various interferences from external electrical or electronics devices. In order to suppress them, the beamforming techniques such as switching, minimum-variance distortionless-response (MVDR), and generalized sidelobe canceler (GSC) have been considered for TPMS. In this paper, we calculate computational complexities of three beamformers and suggest mathematical basis to compare their performance of the complexity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.57-62
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• 2014

Recently, research activities to develop services for providing safety information to the drivers in fast moving vehicles based on various wireless network technologies such as DSRC (Dedicated Short Range Communication), IEEE 802.11p WAVE (Wireless Access for Vehicular Environment) are widely being carried out. This paper presents a proof-of-concept model based on a robot-car for Dilemma Zone Decision Assistant Service using the wireless LAN technology. The proposed model system consists of a robot-car based on an embedded Linux OS equipped with a WiFi interface and an on-board unit emulator, an Android-based remote controller to model a human driver interface, a laptop computer to run a model traffic signal controller and signal lights, and a WiFi access point to model a road-side unit.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.3
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• pp.322-335
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• 2019

Objectives: The goal of this study is to standardize industry, process, and job within work environment measurement information. Methods: We selected 180 work environment measurement reports on 30 industries from a database monitored from 2014 to 2016 by the Korea Industrial Health Association. Ten industrial hygienists, each with over five years of experience in measurement, conducted a primary standardization of 180 reports. Two professional industrial hygienists with more than 20 years of experience each reviewed and revised the results of the primary standardization. We also examined the validity on the usefulness of the standardized database by the two industrial hygienists. Results: The final standardization results were classified into eight major categories, 23 sub-major categories, 39 minor categories, 53 unit categories and 70 sub-unit categories in the Korean Standard Industrial Classification (KSIC) 10th revision. A total of 161 processes were standardized, and there were 148 processes with K2B codes. Standard job was coded into 13 job groups including operator, automobile maintenance, nurse, maintenance, manager, excavating machine operator, forklift driver, radiologist, clinical pathologist, signer, researcher, kitchen assistant, and concrete reinforcement ironworker. Conclusions: Although the standardized information in this study may be only a part of the total information, it can be useful for improvement of the K2B system. Additional research is needed for an ongoing clean-up of data in the K2B and re-calibration and reclassification of standard processes until the future national exposure monitoring system is fully established.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.18-25
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• 2016

As more people have cars, the threat of traffic accidents is posed on men and women of all ages. The main culprit of traffic accidents is driving while intoxicated or drowsy. The method to recognize and prevent the cause of traffic accidents is to use lane detection. In this study, a total of 4,000 frames (day image: 2,900 frames, night image: 1,100 frames) were used to test lane detection. According to the test, in the case of day image, when the threshold of Sobel edge detection technique was detected with second-order differential equation, there was the highest candidate lane detection rate which was 86.1%. In the threshold of Canny edge detection technique, the highest detection rate of 88.0% was found at Low=50, and High=300. In the case of night image, the threshold of Sobel edge detection technique, when horizontal calculation and vertical calculation had second-order differential equation, and when horizontal-vertical calculation had 1.5th-order differential equation, there was the highest detection rate which was 83.1%. In the threshold of Canny edge detection technique, the highest detection rate of 89.9% was found at Low=50, and High=300.