• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1704-1712
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• 1999

This research features efficient detection of obstacles, especially vehicles, in the forward direction of navigation for the development of unmanned automous vehicle. We separate image regions into ground and non-ground planes using the Helmholtz shearing technique in order to reliably exclude regions that do not contain obstacles. We propose a computationally simple and efficient method for the detection of vehicles in the forward direction by analysis of horizontally and vertically projected histograms of residual disparity map obtained from Helmholtz shearing. We have experimented the proposed method on real outdoor stereo data. Experimental results show that our method gives accurate detection of forward vehicles and is computationally very efficient.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.447-452
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• 2005

This paper presents a method that a mobile robot finds location of doors in complex environments and safely traverses the door PCA(Principal Component Analysis) algorithm using the vision information is used for a robot to find the location of door, PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding pattern in data of high dimension. Fuzzy controller using a sonar data is used for a robot to avoid obstacles and traverse the doors.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3048-3050
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• 1999

This paper suggests a position estimating algorithm using mono vision system with projective geometry method. Generally, 3-D information can not be easily extracted from mono vision system which is taken by a camera at a specific point. But this defect is overcome by adopting model-based image analysis and selecting lines and points on the ground as natural landmarks. And this paper suggests a method that estimates position from many natural landmarks by distance error weight function.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1421-1424
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• 2006

By extending the Mandelbrot set for the complex polynomial $$M={c\in C\;:\; _{k\rightarrow\infty}^{lim}P_c^k(0)\;{\neq}\;{\infty}$$ we define the degree-n bifurcation set. In this paper, we formulate the boundary equation of a period-2 component on the main component in the degree-9 bifurcation set by parameterizing its image. We establish an algorithm constructing a period-2 component in the degree-9 bifurcation set and the typical implementations show the satisfactory result with Mathematica codes grounded on the analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.250-252
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• 2004

나노 기술의 개발과 마이크로어레이(microarray)의 등장으로 생물학자동을 한번에 보다 라르고 신속하게, 대량의 실험을 처리할 수 있게 되었다. 이와 발 맞추어 마이크로어레이를 이용한 다양한 실험 방법들이 개발되었다. 형광 염료(fluorescence dye)를 이 용한 관찰 방법 이 널리 이용되고 있으나, 관찰되는 형광 염료의 밝기가 실험 환경(pH, 온도)에 매우 민감하게 반응하며, 단백질을 포함한 많은 분자 물질들이 형광을 내지 않기 때문에 마이크로어레이를 이용한 분석 대상 물질들의 개수가 제한을 받는다. 본 논문에서는 직접적인 형광 염료의 사용 없이, SPR(Surface Plasmon Resonance)을 이용한 마이크로어레이 분석 시스템에서 스팟(spot)의 밝기(intensity)를 측정하기 위한 효율적인 전처리 과정을 제안하고자 한다. 전처리 과정은 크게 프로젝티브 왜곡 효과 제거, 스팟의 위치 추적, 스팟의 영역 추출, 정규화 된 스팟의 밝기 측정으로 나누어진다. 특히, 이러한 과정을 거쳐서 측정된 밝기는 반응 유무의 관찰뿐만이 아니라, 실험 물질의 양적인 측정에도 이용되기 때문에 정확한 스팟의 밝기 측정에 중점을 두고자 한다.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1728-1735
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• 2009

Human action tracking plays an important place in human-computer-interaction, human action tracking is a challenging task because of the exponentially increased computational complexity in terms of the degrees of freedom of the object and the severe image ambiguities incurred by frequent self-occlusions. In this paper, we will propose a novel method to track human action, in our technique, a dynamic background estimation algorithm will be applied firstly. Based on the estimated background, we then extract the human object from the video sequence, and the skeletonization method and Hough transform method will be used to detect the main structure of human body and each part rotation angle. The calculated rotation angles will be used to control a crane in the port, thus we can just control the container crane by using signalman body. And the experimental results can show that our proposed method can get a preferable result than the conventional methods such as: MIT, JPF or MFMC.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.350-351
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• 2018

최근 의료 현장에 인공지능 기술의 도입이 가속화 되고 있다. 특히, 의료영상 분석 분야의 관련된 기 시스템 및 소프트웨어의 패러다임을 변화시키고 있다. 본 연구는 인공지능 기술을 적용하기 위한 학습의료영상 구성을 제안하고 이를 기반으로 X-ray 영상 중 손부위에 적용하여 오른손과 왼손을 판별하는 응용에 적용하였다. 그리고 Deep Learning Algorithm의 CNN을 개선하여 개발한 Advanced GoogLeNet를 적용하여 97%이상의 정확도를 보였다. 본 연구를 통해 얻어진 인공지능에 적용하기 위한 학습데이터 셋 구성과 개선된 알고리즘은 다양한 의료영상분석에 적용하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.556-558
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• 2019

기존 초음파 지방간 분석은 Hepatorenal sonographic index(HI)를 사용하여 지방간을 진단하여 왔다. 이러한 HI 기법에서는 Hepato(간)과 Renal(신장), 두 부분의 영상데이터를 비교 활용하였다면, 본 논문에서는 신장의 영상데이터만을 이용하여, 이의 통계적 특징 벡터만을 활용하여 지방간을 진단을 함으로서 기존의 HI기반 분석대비 편리성과 정확도를 개선코자 Kidney Index(KI) 기반의 분석 기법을 제안한다. 본 논문에서 제안된 KI는 정상간과 지방간을 가진 실제 환자의 초음파 사진(정상간, 지방간 각 30명)을 학습 데이터를 구성하고, 이들 데이터군으로부터 특징 벡터들을 선별하여 머신러닝 기법 중 서포트 벡터 머신(Support Vector Machine)을 통해 학습시켜, 제안된 알고리즘의 유효성을 입증하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.579-582
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• 2010

We propose a method of using the three dimensional characteristic information to classify the front environment in travelling by using the images captured by a CCD camera equipped on a mobile robot. So, this paper proposes the method of deciding the travelling direction of a mobile robot with using input images based upon the suggested algorithm by preprocessing, and verified the validity of the image information which are detected as obstacles by the analysis through neural network.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.2
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• pp.133-138
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• 2014

In this paper, a simple but efficient gait recognition method using spatial-temporal silhouette analysis is proposed. For each image sequence, a background subtraction algorithm and a PBAS(pixel based adaptive segmenter) procedure are first used to segment the moving silhouettes of a walking figure. Then, to identify people, the step count and stride length of walking figure is obtained in silhouette images. Experimental results on a CASIA dataset including 124 subjects demonstrate the validity of the proposed method. Also, the proposed system are believed to have a sufficient feasibility for the application to gait recognition.