• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.82-85
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• 2002

This paper proposes a new position detection method for train speed control using the PDOA(Phase Difference of Arrival). This method aims to apply to AGT(Automated Guide way Transit) systems, operated with driverless. So it is absolutely required to range, calculate and decide a train position precisely. This system consists of VRS (Vehicle Radio Set) and WRS(Wayside Radio Set). The VRS transmits a wireless signal to the WRS, the controller calculate a straight line with the PDOA. Next step calculate an exact position using track DB. This paper includes the concept, configuration, analysis and results of this method.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.4
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• pp.500-505
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• 2011

In this paper, two types of micro-optic submersion detection systems are proposed and demonstrated. The structures are based on the transmission and reflection of incident light, respectively. Two collimators are separated by 10 mm and installed face to face in straight line. The incident light transmits from one side of collimator to the other through the air, but the optical loss is below 1 dB. On the other hand, when the sensors are submersed into water, most of optical power scattered into water. The systems monitor the dramatical power change to alarm the submersion. Reflection type of sensor system has a Bragg grating at the end of the sensor for back-reflection of sensing signal. This is for simple configuration of systems. The performance of two sensor systems are described in detail.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.601-607
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• 2012

The recognition of elevator door is needed for mobile service robots to moving between floors in the building. This paper proposed the sensor fusion approach using LRF (Laser Range Finder) and camera to solve the problem. Using the laser scans by the LRF, we extract line segments and detect candidates as the elevator door. Using the image by the camera, the door candidates are verified and selected as real door of the elevator. The outliers are filtered through the verification process. Then, the door state detection is performed by depth analysis within the door. The proposed method uses extrinsic calibration to fuse the LRF and the camera. It gives better results of elevator door recognition compared to the method using LRF only.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.73-83
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• 2019

In this paper, we propose the augmented reality(AR) based driving navigation based on robust lane detection method to dynamic environment changes. The proposed technique uses the detected lane position as a marker which is a key element for enhancing driving information. We propose Symmetrical Local Threshold(SLT) algorithm which is able to robustly detect lane to dynamic illumination environment change such as shadows. In addition, by using Morphology operation and Connected Component Analysis(CCA) algorithm, it is possible to minimize noises in the image, and Region Of Interest(ROI) is defined through region division using a straight line passing through several vanishing points We also propose the augmented reality aided visualization method for Interchange(IC) and driving navigation using reference point detection based on the detected lane coordinates inside and outside the ROI. Validation experiments were carried out to assess the accuracy and robustness of the proposed system in vairous environment changes. The average accuracy of the proposed system in daytime, nighttime, rainy day, and cloudy day is 79.3% on 4600 images. The results of the proposed system for AR based IC and driving navigation were also presented. We are hopeful that the proposed research will open a new discussion on AR based driving navigation platforms, and thus, that such efforts will enrich the autonomous vehicle services in the near future.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.231-238
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• 2022

Mine detection has been mainly studied with images of the forward-looking sonar. Forward-looking sonar assumes the propagation path of the sound wave as a straight path, creating the surrounding images. This might lead to errors in the detection by ignoring the refraction of the sound wave. In this study, we propose a mine localization method that can robustly identify the location of mines in an underwater environment by considering the refraction of sound waves. We propose a method of estimating the elevation angle of arrival of the target echo signal in a single receiver, and estimate the mine location by applying the estimated elevation angle of arrival to ray tracing. As a result of simulation, the method proposed in this paper was more effective in estimating the mine localization than the existing method that assumed the propagation path as a straight line.

• ETRI Journal
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• v.37 no.6
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• pp.1220-1230
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• 2015

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.687-690
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• 2015

Forward collision warning systems(FCWS) and lane change assist systems(LCAS) need regions of interest for detecting lanes and objects as road regions. Watershed segmentation is effective algorithm that classify the road. That algorithm is split results appear differently depending on Watershed line with local minimum in the early part of the seed. If not road regions or vehicles combined the road's seed, It segment road with the others. For compensate the that defect, It has to adaptive change by road environment. The method is that image segmentate the several of regions of interest. Then It is set in a straight line that is detected in regions of interest. If It was detected cars on seed, seed is adjusted the location. And If It wasn't include the line, seed is adjusted the length for final decision the seed. We can detect the road region using the final seed that selected according to the road environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1879-1886
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• 2016

In this paper, we propose a real-time recognition algorithm of lanes, stop lines and speed bumps on roads for autonomous vehicles. First, we generate a top-view using the image transmitted from a camera that is installed to see the front of a vehicle. To speed up the processing, we simplify the mapping algorithm in constructing a top-view wherein the region of interest (ROI) is concerned. The features of lanes, stop lines and speed bumps, which are composed of lines, are searched in the edge image of the top-view, then followed by labeling and clustering specialized to detect straight lines. The width of lines, distances from the center of a vehicle, and curvature of each cluster are considered to select final candidates. We verify the proposed algorithm on real roads using the commercial car (KIA K7) which is converted into an autonomous vehicle.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.17-23
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• 2018

In this paper, we propose the automatic detection method which find the middle part of tooth crown to start individual tooth segmentation. There have been many studies on the automation of individual tooth segmentation, but there are still many problems for full automation. Detection of middle part of tooth crown used as initial information for individual tooth segmentation is closely related to performance, but most studies are based on the assumption that they are already known or they can be represented by using a straight line. In this study, we have found that the jawbone curve is similar to the tooth alignment curve by spatially analyzing the CT image, and propose a method to automatically detect the middle part of tooth crown. The proposed method successfully uses the jawbone curves to successfully create a tooth alignment curve that is difficult to detect. As the middle part of tooth crown is in the form of a tooth alignment curve, the proposed method detects the middle part of tooth crown successfully. It has also been verified by experiments that the proposed method works well on real dental CT images.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.117-125
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• 2012

Although many studies have been conducted to extract buildings from airborne lidar data, most of them assume that all the boundaries of a building are straight line segments. This makes it difficult to model building boundaries containing curved segments correctly. This paper aims to model buildings containing curved segments as combination of straight lines and arcs. First, two sets of boundary points are extracted by adaptive convex hull algorithm and local convex hull algorithm with a larger radius. Then, arc segments are determined by average spacing of boundary points and intersection ratio of perpendicular lines. Finally, building boundary is modeled through regularization of least squares line or circle fitting. The experimental results showed that the proposed method can model the curved building boundaries as arc segments correctly by completeness of 69% and correctness of 100%. The approach will be utilized effectively to create automatically digital map that meets the conditions of the Korean digital mapping.