• 대한의용생체공학회:의공학회지
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• 제21권2호
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• pp.145-156
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• 2000

본 논문에서는 중앙시상 두뇌 자기공명영상 분할결과를 이용한 3차원 시상 두뇌 자기공명영상의 자동분할기법을 제안한다. 제안된 알고리즘에서는 먼저 3차원 시상 두뇌 자기공명영상의 중앙영상을 분할하고, 분할된 중앙두뇌 자기공명영상을 인접하는 영상에 마스크로 적용한다. 이 때 마스크 적용으로 인하여 인접하는 영상이 절단되는 문제가 발생할 수 있다. 이러한 문제를 해결하기 위하여 절단 영역의 경계점을 검출한 후, 절단 영역에 대한 경로 재설정을 통해 절단 영역을 복원한다. 이러한 경로 재설정을 위해 connectivity-based threshold segmentation algorithm을 사용하였다. 실험결과 제안된 알고리즘의 유용성을 확인할 수 있었다.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.660-667
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• 2006

This paper presents a novel region-based snake method for vessel segmentation. According to geometric shape analysis of the vessel structure with different scale, an efficient statistical estimation of vessel branches is introduced into the energy objective function, which applies not only the vessel intensity information, but also geometric information of line-like structure in the image. The defined energy function is minimized using the gradient descent method and a new region-based speed function is obtained, which is more accurate to the vessel structure and not sensitive to the initial condition. The narrow band algorithm in the level set framework implements the proposed method, the solution of which is steady. The segmentation experiments are shown on several images. Compared with other geometric active contour models, the proposed method is more efficient and robust.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.335-336
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• 2006

In this paper, we propose an active shape image segmentation method for three-dimensional(3-D) medical images using a generation method of the 3-D shape model. The proposed method generates the shape model using a distance transform and a tetrahedron method for landmarking. After generating the 3-D model, we extend the training and segmentation processes of 2-D active shape model(ASM) and improve the searching process. The proposed method provides comparative results to 2-D ASM, region-based or contour-based methods. Experimental results demonstrate that this algorithm is effective for a semi-automatic segmentation method of 3-D medical images.

• 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.

• 대한원격탐사학회지
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• 제21권1호
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• pp.83-89
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• 2005

This study utilized a spatial region growing segmentation and a classification using fuzzy membership vectors to detect the changes in the images observed at different dates. Consider two co-registered images of the same scene, and one image is supposed to have the class map of the scene at the observation time. The method performs the unsupervised segmentation and the fuzzy classification for the other image, and then detects the changes in the scene by examining the changes in the fuzzy membership vectors of the segmented regions in the classification procedure. The algorithm was evaluated with simulated images and then applied to a real scene of the Korean Peninsula using the KOMPSAT-l EOC images. In the expertments, the proposed method showed a great performance for detecting changes in land-cover.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.343-344
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• 2009

The aim in this paper is to show how to extract scalp of a series of brain MR images by using region growing segmentation algorithm. Most researches are all forces on the segmentation of skull, gray matter, white matter and CSF. Prior to the segmentation of these inner objects in brain, we segmented the scalp and the brain from the MR images. The scalp mask makes us to quickly exclude background pixels with intensities similar those of the skull, while the brain mask obtained from our brain surface. We make use of connected threshold method (CTM) and confidence connected method (CCM). Both of them are two implementations of region growing in Insight Toolkit (ITK). By using these two methods, the results are displayed contrast in the form of 2D and 3D scalp images.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 추계학술발표대회
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• pp.429-430
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• 2011

Roughness set theory is a popular topic to use in color-image segmentation. A new popular color image segmentation algorithm is proposed by scientists with the point using traditional histogram and Histon construct roughness set histogram. But, there is still a problem about that is the correlativity of color vector in roughness set histogram, which take an inactive effect in the process of color-image segmentation. Therefore, this paper represents further research based on this and proposed an improved method proved through lot of experiments. The experimental result reduces the correlativity of color vector in roughness set histogram and calculation time remarkably.

• 한국정보통신학회논문지
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• 제22권4호
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• pp.634-640
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• 2018

본 논문에서는 방사선 영상을 기반으로 관심 영역의 자동 추출 알고리즘을 제안한다. 제안 알고리즘은 입력 영상에서 병변부위를 검출하기 위해 세그먼테이션, 특징 추출 및 참조 이미지 매칭을 이용한다. 추출된 영역은 참조 DB에서 일치하는 병변 이미지를 검색하고, 일치된 결과는 칼만 필터 기반의 적합성 피드백을 이용해 병변을 자동 추출한다. 제안 알고리즘은 왼손 x-ray 입력 영상을 기반으로 성장판을 추출하기 위해 왼손 이미지의 윤곽선을 추출하고, 이것은 다중 스케일 해시안 행렬 기반의 세션화를 이용해 후보 영역을 생성 한다. 그 결과, 제안 알고리즘은 관심영역 분할 단계에서는 0.02초로 빠른 분할이 가능하였고, 분할 영상을 기준으로 ROI 추출시 평균 0.53, 강화 단계에서는 0.49초로 매우 정확한 이미지 분할이 가능한 것을 실험을 통해 알 수 있었다.

• 융합신호처리학회논문지
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• 제21권4호
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• pp.209-215
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• 2020

본 논문에서는 에지 향상과 활성 윤곽선을 이용한 용접 비드 영상의 영역화 알고리즘을 제안한다. 제안 방법에서는 에지 향상을 위하여 고주파 필터링과 대비개선을 수행하며, 이후 활성 윤곽선 방법을 적용하면 용접비드만의 영역을 얻을 수 있다. 제안된 알고리즘은 고주파 필터링을 통하여 에지를 검출하며, 대비 개선을 이용하여 검출된 에지를 강화한다. 이렇게 에지 정보를 향상시킨 후에 활성 윤곽선 방법을 적용하여 용접비드 영역을 추출할 수 있다. 제안 알고리즘은 용접 비드 영역화를 위한 기존의 방법들 보다 우수한 성능을 보였다. 제안된 알고리즘의 객관적 신뢰성을 위해 기존의 다양한 고주파 필터링 방법들과 비교하여 용접 비드 영역화가 우수함을 확인하였다. 제안된 방법은 영역화된 용접 비드에 대해 추가적인 절차를 통하여 용접 비드의 품질 평가를 하는데 있어 유용하게 사용될 수 있을 것이다.