• 자동차안전학회지
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• 제14권4호
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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.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.145-148
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• 2011

In this paper, we proposed a search method for structured light pixels of omnidirectional structured light image. Since the omnidirectional structured light image is composed of several circular arc segments, the proposed algorithm searches the structured light pixels in radial direction rather than horizontal or vertical directions. The proposed search algorithm is based on the well-known Bresenham raster algorithm for line drawing in discrete integer space, thereby computation of the algorithm is very efficient. Comparison results between the proposed search algorithm and the conventional horizontal search are presented in experiments.

• 로봇학회논문지
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• 제14권4호
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• pp.301-310
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• 2019

A new algorithm has been propose to detect the reflected light region as disturbances in a real-time vision system. There have been several attempts to detect existing reflected light region. The conventional mathematical approach requires a lot of complex processes so that it is not suitable for a real-time vision system. On the other hand, when a simple detection process has been applied, the reflected light region can not be detected accurately. Therefore, in order to detect reflected light region for a real-time vision system, the detection process requires a new algorithm that is as simple and accurate as possible. In order to extract the reflected light, the proposed algorithm has been adopted several filter equations and clustering processes in the HSI (Hue Saturation Intensity) color space. Also the proposed algorithm used the pre-defined reflected light data generated through the clustering processes to make the algorithm simple. To demonstrate the effectiveness of the proposed algorithm, several images with the reflected region have been used and the reflected regions are detected successfully.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.150-150
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• 2022

This study investigates the roles of decomposition methods on high accuracy in daily rainfall prediction from light gradient boosting machine (LightGBM) algorithm. Here, empirical mode decomposition (EMD) and singular spectrum analysis (SSA) methods were considered to decompose and reconstruct input time series into trend terms, fluctuating terms, and noise components. The decomposed time series from EMD and SSA methods were used as input data for LightGBM algorithm in two hybrid models, including empirical mode-based light gradient boosting machine (EMDGBM) and singular spectrum analysis-based light gradient boosting machine (SSAGBM), respectively. A total of four parameters (i.e., temperature, humidity, wind speed, and rainfall) at a daily scale from 2003 to 2017 is used as input data for daily rainfall prediction. As results from statistical performance indicators, it indicates that the SSAGBM model shows a better performance than the EMDGBM model and the original LightGBM algorithm with no decomposition methods. It represents that the accuracy of LightGBM algorithm in rainfall prediction was improved with the SSA method when using multivariate dataset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4292-4307
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• 2021

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.

• 한국정보전자통신기술학회논문지
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• 제11권6호
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• pp.751-756
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• 2018

본 연구는 입력 영상에서 교통 신호등을 검출하고, 신호등의 색상을 인식하며, 신호를 판별하여 무인 자율주행 차량이나 ITS(Intelligent Transportation System)에 적용할 수 있는 신호등 색상 인식 알고리즘을 제안하였다. 제안된 알고리즘은 교통신호등을 검출하기 위해 CEA(Canny Edge Algorithm)를 이용하여 외곽선을 추출하였고, 신호등의 색상을 인식하고 정확도를 높이기 위하여 HCT(Hough Circle Transform)를 적용하였다. 제안된 방법으로 주행도로상에서 획득한 스트림 영상에 적용한 결과, 우수한 신호등 색상 인식률을 확인할 수 있었다. 특히 입력영상에서 신호등이 존재할만한 ROI(Region Of Interest)로 구분하여 연산시간을 줄일 수 있었고, 신호등과 유사한 영역이라도 원이 검출되지 않거나 HSV 공간에서 V값이 낮아 후보영역에서 탈락시킴으로써 인식률의 정확도를 높일 수 있었다.

• Journal of the Optical Society of Korea
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• 제4권2호
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• pp.89-93
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• 2000

Recently a new signal processing algorithm for white light interferometry was presented. In this paper, the proposed signal processing algorithm was applied for absolute temperature measurement using white light interferometry. Stability testing and absolute temperature measurement were demonstrated. Stability test demonstrated the feasibility of absolute temperature measurement with an accuracy of 0.015 fringe. The test also showed that the absolute temperature measurement system using white light interferometry is capable of obtaining the theoretical minimum detectable change (0.0005 fringe), which is consistent with the performance predicted by the proposed signal processing algorithm.

• 정보과학회 논문지
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• 제44권10호
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• pp.1094-1104
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• 2017

본 논문이 제안하는 동작검출 알고리즘은 빛에 대한 불규칙성을 이용하여 동작영역을 탐색하는 방식으로, 기존 3 way-diff 알고리즘에서 주장한 반사된 빛 영역을 수식화하여 추출한다. 즉, 3 way-diff 알고리즘을 확장한 알고리즘이다. 3 way-diff 알고리즘은 연속된 3개의 이미지를 사용하여 반사된 빛 영역을 추출한다. 이 알고리즘에서 주장하는 반사된 빛 영역이란 이미지 제작과정에서 빛에 의해 발생된 영역으로 모든 사물 주변에 미세하게 생성된다. 이러한 영역을 추출하기 위해 하나의 과정을 보인다. 하지만 이 과정은 단순한 작업일 뿐 빛에 대한 수식이 정의되지 않았다. 본 논문은 3 way-diff 알고리즘에서 주장하는 반사된 빛 영역을 잡음의 일종이라 판단하여 반사된 빛 영역을 추출하는 수식을 정의한다. 제안된 알고리즘과 기존 알고리즘들에 실험을 통해 성능비교를 보인다.

• 한국자동차공학회논문집
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• 제24권2호
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• pp.214-224
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• 2016

This paper proposes an algorithm to effectively detect the traffic lights and recognize the traffic signals using a monocular camera mounted on the front windshield glass of a vehicle in day time. The algorithm consists of three main parts. The first part is to generate the candidates of a traffic light. After conversion of RGB color model into HSI and YCbCr color spaces, the regions considered as a traffic light are detected. For these regions, edge processing is applied to extract the borders of the traffic light. The second part is to divide the candidates into traffic lights and non-traffic lights using Haar-like features and Adaboost algorithm. The third part is to recognize the signals of the traffic light using a template matching. Experimental results show that the proposed algorithm successfully detects the traffic lights and recognizes the traffic signals in real time in a variety of environments.

• 한국컴퓨터정보학회논문지
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• 제16권1호
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• pp.61-69
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• 2011

본 논문은 상대적으로 대비도 차이가 크게 나타나는 역광 이미지에 대해서 Retinex 알고리즘을 적용하여 보정 했을 경우 발생하는 밝은 영역에서의 컬러성분의 손실을 개선하기 위한 새로운 기법을 제안한다. 역광 이미지의 경우 밝은 영역과 어두운 영역에 대한 밝기 차이가 매우 크게 발생하기 때문에 Retinex 알고리즘을 이용하여 영상의 대비도를 향상시킬 경우 밝은 영역에서의 컬러 성분이 손실되는 현상이 발생한다. 이러한 손실을 보완하기 위해서 원본 영상의 밝은 영역에 해당하는 컬러 성분을 Retinex 알고리즘으로 보정된 영상에 추가해준다. K-mean 알고리즘을 이용하여 원본 영상에서의 밝은 영역, 어두운 영역, 중간 영역을 분리하고 밝은 영역에 대해서의 컬러 성분을 추가적으로 복원해 주며, 중간 영역에 대해서는 히스토그램에서의 위치를 기준으로 밝고 어두운 성분에 대한 비율을 고려하여 각 비율에 따라 원본 영상과 Retinex 복원 영상의 밝기 값을 함께 이용하도록 한다. 제안하는 알고리즘의 성능 평가를 위해 역광 현상이 강하게 나타나는 자연영상들을 대상으로 적용하여 기존의 Retinex 알고리즘보다 우수한 성능을 가지고 있음을 보였다.