• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제18권1호
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• pp.27-41
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• 2014

In this paper, we present an efficient numerical method for multiphase image segmentation using a multiphase-field model. The method combines the vector-valued Allen-Cahn phase-field equation with initial data fitting terms containing prescribed interface width and fidelity constants. An efficient numerical solution is achieved using the recently developed hybrid operator splitting method for the vector-valued Allen-Cahn phase-field equation. We split the modified vector-valued Allen-Cahn equation into a nonlinear equation and a linear diffusion equation with a source term. The linear diffusion equation is discretized using an implicit scheme and the resulting implicit discrete system of equations is solved by a multigrid method. The nonlinear equation is solved semi-analytically using a closed-form solution. And by treating the source term of the linear diffusion equation explicitly, we solve the modified vector-valued Allen-Cahn equation in a decoupled way. By decoupling the governing equation, we can speed up the segmentation process with multiple phases. We perform some characteristic numerical experiments for multiphase image segmentation.

• 한국정보전자통신기술학회논문지
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• 제4권4호
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• pp.225-230
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• 2011

본 논문에서는 깊이정보에 기반한 watershed와 영역병합 알고리즘을 이용한 얼굴영역 분할 방법을 제안하였다. 얼굴영역 검출은 영역 분할 단계, 초기 화소 영역 검출 단계, 영역 병합의 세 단계로 구성된다. 입력된 컬러 영상은 제안된 알고리즘에 의해 균일한 작은 영역들로 분할된다. 색도정보와 에지 구속 조건을 사용하여 균일한 영역들을 결합함으로써 얼굴영역을 검출한다. 제안한 알고리즘은 색도정보나 에지정보만을 사용하는 기존 방법에서의 문제점을 해결하였다. 제안한 알고리즘의 성능을 평가하기 위해 컴퓨터 시뮬레이션을 하였으며 정확한 얼굴 영역을 분할할 수 있었다.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1236-1247
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• 2016

Recently, the level set has become a popular method in many research fields. The main reason is that it can be modified into many variants. One such case is our proposed method. We describe a contrast-enhancement method to segment the hippocampal region from the background. However, the hippocampus region has quite similar intensities to the neighboring pixel intensities. In addition, to handle the inhomogeneous intensities of the hippocampus, we used a bias correction before hippocampal segmentation. Thus, we developed a contrast-enhanced bias-corrected distance-regularized level set (CBDLS) to segment the hippocampus in magnetic resonance imaging (MRI). It shows better performance than the distance-regularized level set evolution (DLS) and bias-corrected distance-regularized level set (BDLS) methods in 33 MRI images of one normal patient. Segmentation after contrast enhancement and bias correction can be done more accurately than segmentation while not using a bias-correction method and without contrast enhancement.

• 방송공학회논문지
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• 제21권5호
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• pp.782-791
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• 2016

영상에서 배경으로부터 객체를 추출하는 영상 segmentation 알고리즘은 물체 인식 및 추적 등 다양한 응용분야에서 활용될 수 있다. 본 논문에서는 고정된 카메라에서 다수의 초기 프레임을 참조하여 실시간 객체 segmentation 방법을 제안한다. 먼저 객체와 배경을 분류하는 확률모델을 제안하였으며 초기 프레임 동안에 카메라의 color consistency와 focus 특성을 분석하여 안정적인 segmentation 성능을 증가시켰다. 또한 분류된 객체에서 human의 skeleton 특성을 이용하여 추출 결과를 보정하는 방법을 제안한다. 마지막으로 제안된 알고리즘은 객체 segmentation 실시간 처리를 위하여 복잡도를 최소화하므로 다양한 mobile 단말에 확대 적용 가능하다.

• 한국전자파학회논문지
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• 제11권4호
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• pp.582-591
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• 2000

본 논문에서는 휴대전화기에 의한 인체 영향을 FDTD (시간영역 유한차분법) 해석할 수 있도록 한국인 표준 에 알맞는 인체 두부의 FDTD 모텔 제작 방법을 소개하였다. 한국인 표준에 알맞은 사람의 두부를 MRI 촬영한 다음.2차원 MRI 영상 데이터를 이용하여 2차원 segmentation을 하였다. segmentation은 반자동법을 적용하였 으며 제작된 2차원 se밍nentation 데이터를 토대로 $1mm\times1mm\times1mm$크기의 3차원 고해상도 segmentation 데이터를 제작하였다. 3차원 고해상도 segmentation 데이터를 이용하여 휴대전화기의 사용 상황에 어올리도록 다양한 각도로 기울인 인체 두부의 FDTD 모델을 제작하였다.

• 정보보호학회논문지
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• 제17권6호
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• pp.19-28
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• 2007

본 논문은 지문 데이터베이스를 평가하는데 가장 큰 영향을 미치는 image quality를 측정하는 새로운 방법을 제안한다. 본 논문에서는 image quality를 측정하는 hybrid segmentation 방법을 소개하고, 다양한 지문 데이터베이스에 대해 실험한 결과를 분석한다. 개발한 방법의 객관적인 평가를 위해 NIST에서 제공하는 NFIQ 프로그램을 통해 얻은 결과와 variance와 coherence의 fusion을 이용한 hybrid segmentation 결과를 비교한다. NFIQ는 지문 영상의 품질을 정확하게 측정하지만 결과가 $1{\sim}5$로 세분화되어 있지 못한 문제점을 가지고 있다. 반면 제안하는 hybrid 방법은 NFIQ보다 더 정확하고 세분화된 평가 결과를 제공한다. 두 방법에 의해 실험한 데이터베이스들을 평가한 결과, 동일한 영상에 대해 NFIQ와 hybrid segmentation의 결과가 유사하며 지문 영상의 품질을 세분화하여 측정할 수 있는 점에서 NFIQ보다 뛰어나다고 할 수 있다.

• 한국멀티미디어학회논문지
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• 제23권5호
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• pp.633-640
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• 2020

Defect region segmentation of TFT-LCD images is performed by combining defect pixels detected by a defect detection method into defect region, or by using morphological operations to segment defect region. Therefore, the result of segmentation of the defect region is highly dependent on the defect detection result. In this paper, we propose a method which segments defect regions sequentially according to the possibility of being included in defect regions in TFT-LCD images. The proposed method repeats the process of detecting a seed using the median value and the median absolute deviation of the image, and segments the defect region using the seeded region growing method. We confirmed the superiority of the proposed method to segment defect regions using pseudo-images and real TFT-LCD images.

• 전자공학회논문지B
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• 제33B권10호
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• pp.38-49
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• 1996

In this paper, we propose a fast hierarchical image segmentation using mathematical morphology. The proposed segmentation method is composed of five basic steps; multi-thresholding, open-close by reconstructing, mode operation, marker extraction, and region decision. In the multi-thresholding, an input image is simplified by Lloyd clustering algorithm. The multi-thresholded image then is more simplified by open-close by reconstruction and mode operating. In the region decision, to which region each uncertainty pixel belongs finally is decided by a watershed algorithm. Experimental results show that the quality of the segmentation results by the proposed method is not inferior to that by the conventional method and the average times elapsed by the proposed method can be reduced by one tghird of those elapsed by the conventional method.

• 반도체디스플레이기술학회지
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• 제13권4호
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• pp.49-54
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• 2014

This paper proposes a new color segmentation method of vehicle license plates in the RGB color space. Firstly, the proposed method shifts the histogram of an input image rightwards and then stretches the image of the histogram slide. Secondly, the method separates each of the three RGB color components and performs the adaptive threshold processing with the three components, respectively. Finally, it combines the three components under the condition of making up a segment color and removes noises with the morphological processing. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real vehicle images. The results show that the proposed algorithm is successful for most vehicle images. However, the method fails in some vehicles when the body and the license plate have the same color.

• 한국통신학회논문지
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• 제22권3호
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• pp.410-422
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• 1997

In this paper, we descried a bottom-up document structure analysis method in bilingual Korean-English document. We proposed a character segmentation method based on the layout information of connected component of each character. In many researches, a document has been analyzed into text blocks and graphics. We analyzed a document into four parts: text, table, graphic, and separator. A text is recursively subdivided into text blocks, text lines, words, and characters. To extract the character in bilingual text, we proposed a new method of word of word separation of Korean or English. Futhermore, we used a character merging and segmentation method in accordance with the properties of Hangul on the Korean word blocks. Experimental results on the various documents show that the proposed method is very effectively operated on the document structure analysis and the character segmentation.