• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.254-256
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• 2002

기존의 윤곽선 검출윤곽선 검출방법과는 다른 본 논문에서는 효율적인 방법론을 이용해서 윤곽추출 및 잡음제거 방법론을 제안한다. 제안한 방법론은 전처리과정을 거친후 본 방법론을 적용함으로써 영상 윤곽추출률을 높이고자한다. 특히, 기존의 윤곽선 추출방법인 로버트와 라플라 시안방법을 사용한 후에 미디안 필터를 사용했으며, 제안한 방법은 기존의 윤곽선 추출 필터를 거친 후에 사용하였다. 구체적으로 서술하면 일정한 임계치를 초과하면 흰색으로 대치하고, 그렇치 않으면 검정색으로 대치한다. 기존의 잡음제거과정은 윤곽선 손실은 없었으나 잡음제거가 소량 이루어졌으며, 제안한 방법은 약간의 윤곽선 손실을 보였으나 완전하게 잡음을 제거시킬 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.61-69
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• 2011

Dynamic Time Warping based on Dynamic Programming is the one of the most widely been used to compare the similarity of two patterns. DTW algorithm has two known problems. The one is singularities. And the another problem is the accuracy of the warping path with patterns. Therefore, this paper suggest the solution for DTW algorithm to use a 2nd derivative operator. Laplacian of Gaussian is a kind of a 2nd derivative operator. Consequently, our suggestion method to apply to this operator, more efficient to solve the singularities problems and to secure a accuracy of the warping path. And the result shows a superior ability of this suggested method.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.199-204
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• 2007

In digital radiography, to improve the contrast of digital radiography image, the multi-scale nonlinear amplification algorithm based on unsharp masking is one of the major image enhancement algorithms. In this paper, we used the Laplacian pyramid to decompose a digital radiography(DR) image. In our simulation, the DR image was decomposed into seven layers and the coefficients of the each layer was amplified with nonlinear function. We also imported a noise containment algorithm to limit noise amplification. To enhance the contrast of image, we proposed a new adaptive non-linear gain amplification coefficients. As a result of having applied to some clinical data, a detail visibility was improved significantly without unacceptable noise boosting. Images that acquired with the proposed adaptive non-linear gain coefficients have shown superior quality to those that applied similar gain control method and expected to be accepted in the clinical applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1170-1177
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• 1997

Morphology is a shape preseving filter. Several morphology filter can be made by the combination of morphological basic operation. If we use morphology filter in decimation process for a hierarchical encoder, there are some advantagesin reduction aliasing effects. In this paper, we propose a new hierarchical coder with morphological filtering and vector quantization. And then, firstly, we confirm that CO filtering is the best one among the 4 kinds of morphology filters to reduce aliasing effects in Laplacian pyramid transmission proposed by Burt. Secondly, the those two coders was compared. The results of our simulation show that our new coder surpasser the Laplacian pyramid especially in complex images.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.988-995
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• 2008

A consensus-based feedback linearization method is proposed to maintain a specified time-varying geometric configuration for formation flying of multiple autonomous vehicles. In this approach, there exists no explicit leader in the team, and the proposed control strategy requires only the local neighbor-to-neighbor information between vehicles. The information flow topology between the vehicles is defined by Graph Laplacian matrix, and the formation flying can be achieved by the proposed feedback linearization with consensus algorithm. The stability analysis of the proposed controller is also performed via eigenvalue analysis for the closed-looop system. Numerical simulation is performed for rotary-wing type micro aerial vehicles to validate the performance of the proposed controller.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.34-42
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• 2014

In this paper an embedding algorithm based on commute time is implemented by organizing patches according to the graph-based metric, and its performance is analyzed by comparing with the results of principal component analysis embedding. It is usual that the dimensionality reduction be done within some acceptable approximation error. However this paper shows the proposed manifold embedding method generates the intrinsic geometry corresponding to the signal despite severe approximation error, so that it can be applied to the areas such as pattern classification or machine learning.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.461-470
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• 2010

Semi supervised classification which is a method using labeled and unlabeled data has considerable attention in recent years. Among various methods the graph based manifold regularization is proved to be an attractive method. Least squares support vector machine is gaining a lot of popularities in analyzing nonlinear data. We propose a semi supervised classification algorithm using the least squares support vector machines. The proposed algorithm is based on the manifold regularization. In this paper we show that the proposed method can use unlabeled data efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.179-184
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• 2004

This paper presents an image segmentation algorithm to obtain the 3D body shape data that the grid pattern and the body contour lute in the background image are extracted using the new proposed hybrid method. The body contour line is extracted based on maximum biased anisotropic recognition(MaxBAR) algorithm which recognizes the most strong and robust edges in the image since the normal derivative at the edges is large, while the tangential derivatives can be small. The grid patterns within body contour lines are extracted by grid pattern detection (GPD). The body contour lilies and the grid patterns are combined. The consecutive run test based on heuristic method is used to link the disconnected line and reduce noise line. This proposed segmentation method is more effective than the conventional method which uses a gradient and a laplacian operator, verified with application two conventional method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.275-278
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• 2012

본 논문에서 2D-3D 자동 영상 변환을 위하여 2D 상으로부터 깊이 지도(depth map)을 생성하는 방법을 제안한다. 제안하는 방법은 보다 정확한 깊이 지도 생성을 위해 영상의 전경 깊이 지도(foreground depth map)와 배경 깊이 지도(background depth map)를 각각 생성 한 후 결합함으로써 보다 정확한 깊이 지도를 생성한다. 먼저, 전경 깊이 지도를 생성하기 위해서 라플라시안 피라미드(laplacian pyramid)를 이용하여 포커스/디포커스 깊이 지도(focus/defocus depth map)를 생성한다. 그리고 블록정합(block matching)을 통해 획득한 움직임 시차(motion parallax)를 이용하여 움직임 시차 깊이 지도를 생성한다. 포커스/디포커스 깊이 지도는 평탄영역(homogeneous region)에서 깊이 정보를 추출하지 못하고, 움직임 시차 깊이 지도는 움직임 시차가 발생하지 않는 영상에서 깊이 정보를 추출하지 못한다. 이들 깊이 지도를 결합함으로써 각 깊이 지도가 가지는 문제점을 해결하였다. 선형 원근감(linear perspective)와 선 추적(line tracing) 방법을 적용하여 배경깊이 지도를 생성한다. 이렇게 생성된 전경 깊이 지도와 배경 깊이 지도를 결합하여 보다 정확한 깊이 지도를 생성한다. 실험 결과, 제안하는 방법은 기존의 방법들에 비해 더 정확한 깊이 지도를 생성하는 것을 확인할 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.283-292
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• 2006

Interest about a latest security connection technology rises, and try to overcome security vulnerability Certification about on-line user methods through fingerprint that is biometries information apply. In this study, designs and implements fingerprint recognition system that is invariant to rotation by fingerprint recognition system for certification about on-line user. Proposed method focused in matching process through pre-process of fingerprint image, feature point extraction. Improved process time and correct recognition rate in fingerprint recognition system that is invariant to rotation presented in existing study. Also, improved noise, distortion problems that happen in preprocess of existing study applying directional Laplacian filter.