• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1995년도 학술대회
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• pp.143-148
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• 1995

In this paper, we describe a fast 3D video segmentation method using mathematical morphology. The proposed 3D video segmentation algorithm is composed of intra-frame segmentation step and inter-frame segmentation step. In the intra-frame segmentation step, the first frame is segmented using the fast hierarchical segmentation method. Then, in the inter-frame segmentation step, the next frames are segmented using markers that are extracted from the difference of previous segmentation result and simplified present image. Experimental results show that the proposed method has more fast structure and is suitable for video segmentation.

• 디지털산업정보학회논문지
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• 제5권2호
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• pp.157-165
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• 2009

Existing methods for image segmentation using diffusion can't preserve contour information, or noises with high gradients become more salient as the umber of times of the diffusion increases, resulting in over-segmentation when applied to watershed. This thesis proposes a method for image segmentation by applying morphology operation together with robust anisotropic diffusion. For an input image, transformed into LUV color space, closing by reconstruction and anisotropic diffusion are applied to obtain a simplified image which preserves contour information with noises removed. With gradients computed from this simplifed images, watershed algorithm is applied. Experiments show that color images are segmented very effectively without over-segmentation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1972-1975
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• 2003

Video segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries. But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes image segmentation improvement by selective application structuring element of mathematical morphology.

• 전자공학회논문지 IE
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• 제43권2호
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• pp.39-48
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• 2006

본 논문은 공간적 자동 객체 분할의 개념과 클러스터링 개념을 가진 웨이브렛 형태학 알고리즘을 제안하였다. 제안된 알고리즘을 이용하여 컬러 얼굴을 분할할 때 영상을 단순화하였으며, 또한 사용자의 조작 없이 실시간적으로 분할해 검출할 수 있도록 공간적 특성을 이용하였다. 이것은 HSV 컬러 모델을 이용하여 영상에서 잡음으로 간주되는 작은 부분을 제거하고, 얼굴영상 이외의 부분을 제거하기 위해 웨이브렛 형태학을 적용하였다. 본 논문은 웨이브렛 형태학 알고리즘과 형태학 알고리즘을 비교하였으며, 그리고 HSV 컬러 공간 모델을 적용한 영상에서 얼굴 객체 부분을 정확하게 검출함을 보였다.

• Journal of Electrical Engineering and Technology
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• 제11권1호
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• pp.234-240
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• 2016

We propose a novel framework for markerless camera-based games. By using a visual camera, our method may yield robust human body segmentation with high performance comparable to the segmentation using depth cameras. The edges of human bodies are detected by subtracting gradient backgrounds, and human body regions are segmented by the operations based on mathematical morphology. Collisions between detected regions and virtual objects are determined by finding the colliding time using intra-frame positions of virtual objects. Experimental results show that the proposed method may produce robust segmentation of human bodies, thereby and the collision responses are more accurate than previous methods. Therefore, the proposed framework can be widely used in camera-based games requiring high performance.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권6호
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• pp.523-531
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• 2005

확산(Diffusion)을 이용한 기존의 칼라영상 분할은 확산의 횟수가 반복될수록 경계선 정보가 적절히 유지되지 못하거나 잡음을 제거하지 못함으로써 워터쉐드(Watershed) 알고리즘을 적용하는 경우, 과분할을 피할 수 없다는 단점을 갖고 있다. 본 논문에서는 수리 형태학(Mathematical Morphology)과 비선형 확산(Non-Linear Diffusion)을 함께 적용하여 과분할의 문제점을 제거한 워터쉐드 결과를 얻을 수 있는 칼라영상 분할방법을 제안한다. 임의의 칼라 영상을 LUV 색상공간으로 변환하여, 그 각각의 색상공간에 수리 형태학을 응용한 재구성에 의한 닫힘(Reconstruction) 연산과 비선형 확산을 함께 적용하여 경계선을 적절히 유지하면서 잡음을 제거한 단순 영상을 획득할 수 있다. 이 영상에서 칼라 영상의 기울기(Gradient) 정보를 획득하고, 워터쉐드 알고리즘을 적용하여 영상을 분할한다. 실험 결과, 기존의 방법보다 과분할이 현저히 제거되고, 칼라 영상이 매우 효과적으로 분할됨을 확인하였다

• 전자공학회논문지S
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• 제34S권7호
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• pp.78-88
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• 1997

A three dimensional-two spatical dimensions plus time-image segmentation is widely used in a very low bit rate image sequence coding because it can solve the region correspondence problem. Mathematical morphology is a very efficient tool for the segmentation because it deals well with geometric features such as size, shape, contrast and connectivity. But if the motion in the image sequence is large in time axis, the conventional 3D morphological segmentation algorithm have difficulty in solving region correspondence problem. To alleviate this problem, we propose the hierarchical image sequence segmentation algorithm that uses the region motion information. Since the motion of a region in previous level affects that in current level uses the previous motion information to increase region correspondence. Simulation result shows improved performance for sequence frames with large motion.

• 전자공학회논문지B
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• 제33B권8호
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• pp.68-80
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• 1996

In this paper, we propose a novel color image segmentation algorithm based on clustering in 3-dimensional color space employing the mathematical morphology. More specifically, since we take into account the topological properties such as the shape, connectivity and distribution of clusters in the clustering process, the number of clusters in the color cube, as well as their centers, can be easily obtained, without a priori knowledge on the input images. Intensive computer simulation has been performed and the results are discussed in this paper. The resutls of the simulation on the images in various color coordinates show that the segmentation is independent of the choice of color coordinates and the shape of clustes. Segmentation results of the vector quantizer are also presented for the comparison purpose.

• 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.

• 한국의학물리학회지:의학물리
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• 제15권2호
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• pp.70-76
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• 2004

간 영역을 다른 복부 장기들로부터 정확히 분할한 후 간 내부의 종양을 감별 분할하므로써 간암을 조기 발견하는 데 도움을 준다. 본 논문은 복부의 모포러지컬 특성을 이용하여 효과적인 완전 자동 간 분할을 수행할 수 있는 알고리즘을 제안한다. 전처리 단계로서 다봉성 히스토그램 분할을 수행하고 복부의 모폴러지 좌표를 찾기 위해 척추를 분할한다. 다음으로 간 영역을 C-class maximum a posteriori (MAP) decision과 이진 모폴러지 필터링에 의해 추출한다. 자동으로 분할된 간 영역을 평가하기 위해 영역 에러율(Average Error Rate)과 회전 이진 영역 투영 매칭법(Rotational Binary Region Projection Matching; RBRPM)에 의한 상관 계수를 사용한다. 실험 결과는 제안한 알고리즘에 의해 획득한 완전 자동 간 분할과 수동 간 분할사이에 매우 유사한 결과를 보였다.