• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.760-762
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• 2004

본 논문에서 CT영상에서 간 영역을 자동적으로 분할할 수 있는 방법을 제안한다. 밝기의 특성을 이용하여 초기 관심 영역을 추출하기 위해 ATI(Automatic Threshold Intensity)기법을 사용하였다. 간 영역을 최종적으로 추출하기 위해 블럽 컬러링 기법을 사용하였다 기존 블럽 컬러링의 연산속도를 개선하기 위해서 Recoloring table을 이용하였다 제안된 방법을 이용하여 실험한 결과로 간 영역 추출의 성공률 90%를 얻었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.246-249
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• 2011

페이징을 이용한 가상 메모리 환경에서는 프로세스가 사용하는 가상 페이지가 임의의 물리 페이지로 매핑이 되므로 캐시 인덱스 충돌로 인한 캐시 미스율이 증가한다. 이를 하드웨어의 지원 없이 해결하기 위해 페이지 컬러링 기술은 처음 연구되기 시작하였고, 지금까지도 꾸준히 연구되고 있다. 이러한 페이지 컬러링 기술은 컬러링 정책을 먼저 정해놓고 컬러링을 하는 정적 페이지 컬러링, 그리고 동적프로파일링을 통해 프로세스의 데이터 영역 접근 패턴을 파악하고 이를 통해 실시간 컬러링을 하는 동적 페이지 컬러링으로 나눌 수 있다. 하지만 두 가지 방법 모두 다음과 같은 단점이 존재한다. 먼저 정적 페이지 컬러링은 프로세스의 동작을 프로파일링 할 수 없기 때문에 컬러링으로 인한 효율을 극대화시킬 수 없고, 동적 페이지 컬러링은 동적 프로파일링을 하고 이를 통해 재컬러링(recoloring) 하는 오버헤드가 존재한다. 이러한 문제를 해결하기 위해서, 본 논문에서는 실행 코드 영역 프로파일링을 통한 MFU(Most Frequently Used) 기반 페이지 컬러링 기법을 제안한다. 이 기법은 동적으로 프로세스 코드 영역을 프로파일링 하여 실행 점유율이 높은 영역을 알아낸 뒤, 이를 기반으로 정적 페이지 컬러링을 하는 방식이다. 따라서 본 논문에서 제안한 기법은 기존의 기법들이 가진 단점을 해결하고, 캐시 성능을 향상시킬 것으로 기대된다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.149-159
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• 2008

We present new methods which transfer the color style of a source image into an arbitrary given reference image. Misidentification problem of color cause wrong indexing in low saturation. Therefore, the proposed method do indexing after Image separating chromatic and achromatic color from saturation. The proposed method is composed of the following four steps : In the first step, Image separate chromatic and achromatic color from saturation using threshold. In the second step, image of separation do indexing using cylindrical metric. In the third step, the number and positional dispersion of pixel decide the order of priority for each index color. And average and standard deviation of each index color be calculated. In the final step, color be transferred in Lab color space, and post processing to removal noise and pseudo-contour. Experimental results show that the proposed method is effective on indexing and color transfer.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.91-101
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• 2013

This paper proposes a new re-coloring method for the people with the red-green color vision deficiency (CVD). These people have difficulty in discriminating the red and green colors since they abnormally perceive the hue and luminance value of the colors. We introduce a color transformation that adjusts the hue and luminance value in HSV color space. The color transformation is determined according to the severity of CVD. Our aim is to maintain the color differences in original image while maintaining the recolored image to be natural to the people with normal color vision. Experimental results show that the proposed method can yield more comprehensible images for the people with red-green CVD while maintaining the naturalness of the recolored images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.1-8
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• 2022

Recently, Google MedeiaPipe presents a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Though neural network related to hair segmentation is relatively small size, it produces a high-quality hair segmentation mask that is well suited for AR effects such as a realistic hair recoloring. However, it has undesirable segmentation effects according to hair styles or in case of containing noises and holes. In this study, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood function. It is further optimized according to graph cuts algorithm and initial hair region is obtained. Finally, clustering algorithm and image post-processing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. The proposed method is applied to MediaPipe hair segmentation pipeline.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.67-73
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• 2012

Local color transfer is the process of assigning a given color to a local region in a target image. The local region that contains the given color has to be segmented. Conventionally, the segmentation of the corresponding local region in a target image is based on the color distance. The region which is the closest in color distance is separated. However, since the close range of color distance separating a given color from target image is ambiguous and uncertain, color distortion is often generated around a separated local region. Therefore, this paper addresses the problem of segmentation in a local color transfer. To prevent color distortion, a modified color influence map is proposed with color categories. First, the target image is roughly segmented using a color category map, which groups similar colors in color space. It restricts the color transfer to a specific color category according to a given color. Second, modified color influence map assigning different weight to lightness and chroma, respectively, is used instead of Euclidian color distance. Then, by combining a modified color influence map and color category map filtered with anisotropic diffusion, a local region that contains a given color can be segmented more strictly than conventional method.