• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.262-264
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• 2003

얼굴영상을 효율적으로 처리하기 위해선 먼저 입력영상에서 얼굴영역과 얼굴을 구성하는 각 기관을 검출하는 전처리과정이 필요하다. 본 논문에서는 얼굴의 크기와 얼굴의 회전, 조영의 변화가 어느 정도 허용되고 피부색 배경이 얼굴에 병합된 경우에도 얼굴영역과 얼굴기관(눈, 입)을 강건하게 검출할 수 있는 방법으로, 입력영상에 따른 적응적 칼라 색상정보와 얼굴기관의 부분 템플릿매칭을 조합한 알고리즘을 제안한다. 변환된 HSV 칼라 좌표계상의 대역적 피부색상 정보와 히스토그램을 이용한 적응적 피부색상 정보로 얼굴영역을 검출한 뒤, 얼굴영역 안에서 입술색상 정보로 도출된 입술영역의 X축 기울기를 이용해 회전얼굴을 보정하고, 양안의 조합으로 이루어진 부분 템플릿을 이용해 눈을 검출한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.295-298
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• 2009

웨이블렛 변환(Wavelet Transform)은 영상압축에 효율적인 방법으로 알려져 있으며 lifting scheme을 이용해서 쉽게 구현이 가능하다. 가장 널리 쓰이는 방법으로는 Daubechies 5/3 필터가 있고, 이를 바탕으로 하여 영상의 기하학적인 특성을 이용한 적응적 예측 방법이 많이 소개되었다. 본 논문에서는 적응적 예측을 위해 템플릿 매칭을 적용한 새로운 알고리즘을 제안하였다.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.621-624
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• 1999

This paper describes a distance estimation method of object's motion in soccer image sequence by tracking field features. And we quantitatively evaluate the estimation accuracy We suppose that the input image sequence is taken with a camera on static axis and includes only zooming and panning transformation between frames. Adaptive template matching is adopted for non-rigid object tracking. For background compensation, feature templates selected from reference frame image are matched in following frames and the matched feature point pairs are used in computing Affine motion parameters. A perspective displacement field model is used for estimating the real distance between two position on Input Image. To quantitatively evaluate the accuracy of the estimation, we synthesized a 3 dimensional virtual stadium with graphic tools and experimented on the synthesized 2 dimensional image sequences. The experiment shows that the average of the error between the actual moving distance and the estimated distance is 1.84%.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.109.2-109
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• 2001

In the PCB assembly lines, as components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. The automatic optical inspection(AOI) gradually becomes the alternative in the PCB assembly line. In Particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching, Fourier analysis, edge analysis, geometric feature recognition or optical character recognition (OCR), which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the ...

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.291-297
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• 2018

In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.94-102
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• 2015

Optical camera communication (OCC) is an extension of Visible Light Communication. Different from traditional visible light communication, optical camera communications is an almost no additional cost technology by taking the advantage of build-in camera in devices. It was became a candidate for communication protocol for IoT. Camera module can be easy attached to IoT device, because it is small and flexible. Furthermore almost smartphone equip one or two camera for both back and font side with high quality and resolution. It can be utilized for receiving the data from LED or positioning. Actually, OCC combines illumination and communication. It can supply communication for special areas or environment where do not allow Radio frequency such as hospital, airplane etc. There are many concept and experiment be proposed. In this paper we proposed utilizing Android smart-phone camera for receiver and introduce new approach in modulation scheme for LED at transmitter. It also show how Manchester coding can be used encode bits while at the same time being successfully decoded by Android smart-phone camera. We introduce new data frame format for easy decoded and can be achieve high bit rate. This format can be easy to adapt to performance limit of Android operator or embedded system.