• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.7
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• pp.89-96
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• 2002

In this paper, the ADI(Adaptive De-interlacing) algorithm is proposed, which improves visually and subjectively horizontal and vertical edges of the image processed by the ELA(Edge Line-based Average) method. This paper also proposes a VLSI architecture for the proposed algorithm and the architecture designed through the full custom CMOS layout process. The proposed algorithm is verified using C and Matlab and implemented using $0.6{\mu}m$ 2-poly 3-metal CMOS standard libraries. For the circuit and logic simulation, Cadence tool is used.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1992.06a
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• pp.443-446
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• 1992

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.873-876
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• 2000

본 논문에서는 양방향 움직임 보상에 의한 필드 보간(bi-directional motion-compensated field interpolation) 방법을 사용한 효과적인 디인터레이싱(de-interlacing) 기법을 제안한다. 움직임 추정(motion estimation)을 이용한 일반적인 디인터레이싱 기법은 서로 다른 샘플링 격자(sampling grid) 관계인 연속한 두 필드(field)들간의 움직임 추정을 위해 line average 같은 비교적 간단한 형태의 디인터레이싱 기법이 선행된다. 그러나, 제안한 방법은 보간할 필드(the interpolated field)의 전후 필드들의 같은 샘플링 관계인 존재하는 스캔 라인(the existing scan line)들 사이에서만 움직임 추정이 이루어지므로 구현이 용이하다. 이때 구해진 움직임 벡터는 양방향 움직임 추정을 위한 초기 값으로 사용되어 진다. 제안한 알고리듬은 기존의 움직임 정보를 이용한 기법에 비해 구현이 용이하며, 카메라 움직임이 있는 panning, zooming 영상에 특히 효율적이다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.114-125
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• 1998

In this study, for the first time, we propose the ADI(Adaptive De-Interlacing) algorithm, which improves visually and subjectively, horizontal and vertical edges on the image processed by the ELA (Edge Based Line Average) method. The proposed ADI algorithm enlargesthe window size to 5*3 in order to utilize the feature of the continuity of edges, and the adaptive interpolator is employed to decide adaptiely horizontal, diagonal, and vertical edges. Based on the results of the compter simulation, it is confimed that the new ADI algorithm improve the PSNR by 0.5dB in the Lena image with 512*512 size and by 0.4dB in the sequence image of a salesman, respectively. For the horizontal and vertial edges on the still and salesman sequence images, the proposed ADI algorithm has better visulal improvement than the conventional ELA algorithm.

• The Korean Journal of Cytopathology
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• v.7 no.1
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• pp.107-110
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• 1996

Cytologic findings of 2 cases of metastatic leiomyosarcoma diagnosed by fine needle aspirtion cytology are reported. Case 1 is pleomorphic leiomyosarcoma which had metastsized to the liver from the stomach of a 54-year-old male patient. The cytologic features showed highly cellular aspirates with nuclear pleomorphism and interlacing pattern. Case 2 is low grade leiomyosarcoma that occurred in the uterus of a 43-year female patient and metastsized to both lungs. The aspirates were less cellular than that of case 1, and showed spindle cells with minimal pleomorphism, but ceil block revealed interlacing patterns of smooth muscle cells with occasional mitosis.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.199-202
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• 2009

This paper proposes a novel adaptive algorithm for deinterlacing. In the proposed algorithm, the previously developed Enhanced ELA [6], Chen [9] and Li [10] algorithms were used as a basis. The fundamental mechanism was the selection and application of the appropriate algorithm according to the correlation with the previous and next field using temporal information. Extensive simulations were conducted for video sequences and showed good performance in terms of peak signal-to-ratio (PSNR) and subjective quality.

• Science of Emotion and Sensibility
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• v.11 no.1
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• pp.123-129
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• 2008

The purpose of this study is to analyse the effect of weaving preparatory process characteristics on the PET fabric sensibility through assessment of handle, garment formability and sewability for the enhancement of the physical property of the PET fabrics. For this purpose, eleven fabric specimens processed on the interlacing, pirn winder, 2-for-1 twister, weaving and dyeing and finishing processes were prepared and processing tension and interlacing intensity after each process were measured with various processing conditions.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.7-10
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• 2006

격행 주사 방식은 제한된 대역폭을 효율적으로 사용찬 수 있기 때문에 NTSC(National Television System Committee), PAL(Phase Alternation Line), 그리고 SECAM(Sequentiel couleur a Memoire)을 포함한 다양한 TV 방송 표준에서 넓게 이용되어지고 있다. 격행 주사 방식을 이용하면 같은 대역폭을 사용하는 동안에 프레임 율을 2배로 늘일 수 있으나 이 방식은 주사 방식의 특징 때문에 영상의 화질 열화를 가져온다. 이러한 화질 열화를 방지하기 위해 기존의 많은 디인터레이싱(De-interlacing) 기법들이 소개 되었다. 본 논문에서는 정교한 DOI(Direction Oriented Interpolation)기법을 제안한다. 제안하는 알고리즘은 기존의 알고리즘보다 안정적이고 에지의 방향을 좀 더 정교하게 찾는 특징이 있다. 실험 결과 제안한 방식은 주관적인 화질뿐만 아니라 객관적인 성능도 우수함을 알 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.568-570
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• 2003

비월주사(interlaced)에서 순차주사(progressive)로의 변환을 디인터레이싱(de-interlacing)이라 한다. 제안하는 방식은 움직임 검출을 통해 움직임이 없는 영역에서는 앞선 필드정보를 이용하여 별도의 계산량 없이 디인터레이싱을 하게 되며, 움직임이 있는 영역에서는 공간정보(spatial information)를 이용하여 디인터레이싱하는 ELA(Edge based line average) 방식과 양방향 움직임 추정(bi-directional motion estimation)을 통한 시간정보(temporal information)를 이용하여 디인터레이싱하는 움직임 보상방법 간의 가중합산(weighted summation)을 이용하여 디인터레이싱을 수행하는 방법을 제안한다. 이 때 가중치(weight)는 공간 및 시간 정보 모두를 사용하여 결정되어지며, 이렇게 결정되어진 가중치를 통해 각 방식의 단점을 극복하게 된다. 이러한 가중합산을 이용한 방법은 높은 계산복잡도 없이 단순한 구현을 통해 다양한 조건에서 높은 성능의 디인터레이싱이 가능토록 해주며, 그 하드웨어 구현을 용이하게 해준다.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.