• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.358-362
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• 2014

이안식 일체형 입체카메라는 줌인 시 고정된 컨버전스 포인트로 인해 촬영된 영상 시청할 때 어지러움을 유발하는 시각적 불편이 발생할 수 있다. 본 논문에서는 이안식 일체형 입체카메라에서 줌인 시 발생되는 시각적 불편과 거리감의 변동을 방지하기 위해 3DCG환경에서 컨버전스 포인트 이동값에 대한 실험을 한다. 거리별 컨버전스 포인트 이동에 따른 입체영상을 시청하고 평가하는 주관 평가를 실시하여 시각적 불편을 최소화하는 컨버전스 포인트 조정기법을 제안할 수 있는 근거를 마련하고자 한다.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.357-365
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• 2019

In this paper, we suggest the tracking method of moving multi-objects in maritime environments. The image acquisition is conducted using IR(InfraRed) camera sensors on an airborne platform. Under the circumstance of maritime, the qualities of IR images can be significantly degraded due to the clutter influence, which directly gives rise to a tracking loss problem. In order to reduce the effects from the clutters, we introduce a technical approach under Man-In-The-Loop(MITL) system for enhancing the tracking performance. To demonstrate the robustness of the proposed approach based on VTG(Valid Tracking Gate), the simulations are conducted utilizing the airborne IR video sequences: Then, the tracking performances are compared with the existing Kalman Filter tracking techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6018-6033
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• 2018

Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.145-147
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• 2018

다수의 일반 카메라로 촬영한 영상들로 360도 영상을 제작하는 경우 다수의 영상 간 동일한 영역을 찾고 기하학 보정을 위한 영상 스티칭 기술이 필요하다. 영상 스티칭 기술은 여러 영상에서 추출한 특징점들의 유사도를 비교하여 영상들을 이어 붙여 큰 하나의 영상으로 만드는 것이다. 본 논문에서는 비콘이 부착된 공연장을 가정하여, 비콘을 통해서 촬영자의 위치를 대략적으로 파악하고, 사용자가 어플리케이션을 통하여 전송한 영상과 영상의 방위각, FOV(Field Of View)들을 이용하여 실내에서 촬영된 영상들을 스티칭 대상 영상들로 필터링하는 방법을 제안한다.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.130-134
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• 2020

This paper proposes a new method for the digit recognition on a 7-segment display. The proposed method uses morphological processing that dilates segments of digits and connects them into strokes. The digits are extracted by connected component analysis and finally, template matching method recognizes the extracted digits. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. Experiments were conducted by using various 7-segment LED displays and 7-segment mono LCD displays. The results show that the proposed method is successful for the digit recognition on the 7-segment displays.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.849-852
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• 2021

This paper presents a vision based tire mold inspection system where mold defects are inspected and the sizes of specific parts of the mold are measured. There are a lot of challenging issues as letters and pictures of intaglio are engraved on a bright surface of the tire mold. To solve the issues, we carefully selected a line-scan camera and a line light. In addition, we used PLC to control the mechanical parts. The developed system provides inspection of misspelled and deformed letters as well as a variety of the functions such as size measurement of engraved regions and inspection report file creation.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1302-1304
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• 2013

본 논문에서는 로봇이 정해진 폐구간을 이동하기 위해서 위에서 아래로 촬영한 카메라 정보를 활용한다. 로봇을 특정위치로 이동시키기 위해서는 카메라를 제어하는 서버 시스템과 로봇의 위치를 인식하기 위한 마크가 필요하다. 서버는 로봇의 위치를 로봇으로 인식하는 마크의 색 값으로 카메라로부터 인지하고 로봇에 위치 이동 명령을 수행할 서버와 로봇이 네트워크를 통해 Planning을 수행한다. 본 연구에서 휴머노이드 로봇인 나오와 로봇에 위치를 촬영할 카메라 그리고 이미지 처리를 하기 위해 OpenCV와 이동 알고리즘으로 $A^*$를 활용하여 Planning을 구현한다.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.22-26
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• 2022

This paper proposes a new method for the recognition of road surface marks and numbers. The proposed method designates a region of interest on the road surface without first detecting a lane. The road surface markings are extracted by location and size using a connection component analysis. Distortion due to the perspective effect is minimized by normalizing the size of the road markings. The road surface marking of the connected component is recognized by matching it with the stored road marking templates. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the recognition of road surface marks and numbers.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.6-15
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• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.