• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.160-174
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• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.430-443
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• 2013

The recognition of current position and road surrounding of car is very important to driver for safe driving. This paper presents the recognition technique of the road traveling environment using position information hiding and viewpoint transform that monitors the information of road furniture and signature and notifies them to driver. The proposed scheme generates the road images into which the position information are hided, from car camera and GPS module and provides the road information to driver through the viewpoint transformation and the road signature detection. The driving tests with camera and GPS module verified that the position information hiding takes about 66.5ms per frame, the detection rate of road signature is about 95.83%, and the road signature detection takes about 227.45ms per frame. Therefore, we know that the proposed scheme can recognize the road traveling environment on the road video with 15 frame rate.

• Journal of IKEEE
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• v.18 no.2
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• pp.291-297
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• 2014

Since hand gesture recognition was realized thanks to improved image processing algorithms, sign language translation has been a critical issue for the hearing-impaired. In this paper, we extract human hand figures from a real time image stream and detect gestures in order to figure out which kind of hand language it means. We used depth-color calibrated image from the Kinect to extract human hands and made a decision tree in order to recognize the hand gesture. The decision tree contains information such as number of fingers, contours, and the hand's position inside a uniform sized image. We succeeded in recognizing 'Hangul', the Korean alphabet, with a recognizing rate of 98.16%. The average execution time per letter of the system was about 76.5msec, a reasonable speed considering hand language translation is based on almost still images. We expect that this research will help communication between the hearing-impaired and other people who don't know hand language.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.101-106
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• 2017

In this paper, we present Emergency exit signs are installed to provide escape routes or ways in buildings like shopping malls, hospitals, industry, and government complex, etc. and various other places for safety purpose to aid people to escape easily during emergency situations. In case of an emergency situation like smoke, fire, bad lightings and crowded stamped condition at emergency situations, it's difficult for people to recognize the emergency exit signs and emergency doors to exit from the emergency building areas. This paper propose an automatic emergency exit sing recognition to find exit direction using a smart device. The proposed approach aims to develop an computer vision based smart phone application to detect emergency exit signs using the smart device camera and guide the direction to escape in the visible and audible output format. In this research, a CAMShift object tracking approach is used to detect the emergency exit sign and the direction information extracted using template matching method. The direction information of the exit sign is stored in a text format and then using text-to-speech the text synthesized to audible acoustic signal. The synthesized acoustic signal render on smart device speaker as an escape guide information to the user. This research result is analyzed and concluded from the views of visual elements selecting, EXIT appearance design and EXIT's placement in the building, which is very valuable and can be commonly referred in wayfinder system.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.91-98
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• 2011

Road signs are part of the traffic facilities intended to guide drivers to their destinations in a safe and comfortable manner. Due to the creation of new routes, changes to the old routes, and the deterioration of road signs, road signs do require efforts to do ongoing field investigations and put the results in a database. The purpose of this study was to propose methodologies to do field investigations and build a database for road signs efficiently. For that purpose, a mobile mapping system was designed for field investigations. The designed mobile mapping system was comprised of three cameras to produce image information about road signs, GPS/IMU/DMI to obtain information about the position and attitude of a vehicle, and a laser scanner to generate information about the locations of road signs and routes. Also proposed in the study was a procedure to automatically detect the areas of road signs in the road signs images and recognize their characters.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.138-144
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• 2014

Now, Autonomous unmanned vehicle has become an issue in next generation technology. 2D Laser scanner as the distance measurement sensor is used. 2D Laser scanner detects the distance of 80m, measured angle is -5 to 185 degree. Laser scanner detects only the plane, but using motor swings. As a result, traffic signs detect and analyze patterns. Traffic signs when driving at low speed, shape of the detected pattern is very similar. By shaking the laser scanner, traffic signs and other obstacles became clear distinction.

• Current Optics and Photonics
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• v.1 no.3
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• pp.196-202
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• 2017

Corona discharge is always a sign of failure processes of high-voltage electrical apparatus, including those utilized in electric railway systems. Solar-blind ultraviolet (UV) cameras are effective tools for corona inspection. In this work, we present an automatic railway corona-discharge detection system based on solar-blind ultraviolet detection. The UV camera, mounted on top of a train, inspects the electrical apparatus, including transmission lines and insulators, along the railway during fast cruising of the train. An algorithm based on the Hough transform is proposed for distinguishing the emitting objects (corona discharge) from the noise. The detection system can report the suspected corona discharge in real time during fast cruises. An experiment was carried out during a routine inspection of railway apparatus in Xinjiang Province, China. Several corona-discharge points were found along the railway. The false-alarm rate was controlled to less than one time per hour during this inspection.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.139-141
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• 2014

지능형 차량 시스템에 있어서 교통 표지판 검출/인식은 매우 중요한 요소들 중의 하나이다. 따라서 주행 중인 차량에서 카메라로부터 취득한 영상을 이용하여 교통 표지판을 인식하는 여러 가지 영상인식 알고리즘들이 개발되고 있다. 하지만 이러한 알고리즘은 표지판의 색상 값이 날씨와 시간에 따른 조도와 컬러의 변화에 따라 성능이 크게 변한다는 점에서 어려움을 겪고 있다. 따라서 본 논문은 환경 변화에 강인한 교통 표지판 검출 및 인식 알고리즘을 제안한다. 구체적으로, 표지판 검출을 위하여 제안하는 알고리즘에서는 색상과 형태 정보를 이용하여 교통 표지판 후보군을 찾는다. 여러 색상 임계값에 대하여 영상 피라미드 형태를 만들고, 모든 피라미드 영상들에 대해서 인식 알고리즘을 수행함으로써 실외 빛에 변화에 강인하게 한다. 교통 표지판 후보군을 찾은 후, 후보군들을 Linear SVM을 통해 학습함으로써 교통 표지판인지 아닌지 분류해낸다. 실험 결과는 제안하는 알고리즘이 정확하게 교통 표지판을 인식하고, 동시에 실외 빛의 변화에 상관없이 강인하게 표지판을 인식함을 보여준다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.598-601
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• 2010

개인용 단말기 디스플레이 상의 광고물 객체의 기준점 설정하여 좌표 값, 색상 값을 받은 후 그 정보를 기반으로 광고물의 경계선을 추출한다. 경계선에서 추출된 4 모서리의 좌표와 거리 측정기를 통하여 측정한 거리 값을 통해 여러 위치에서도 광고물의 면적을 측정하는 시스템을 구현한다.