• Journal of Biomedical Engineering Research
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• v.26 no.6
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• pp.383-391
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• 2005

Age-related White Matter Changes (WMC) on Magnetic Resonance Imaging (MRI) are known to appear frequently in Multiple sclerosis (MS) and Alzheimer's disease and to be related to cognitive impairment. The characterization of these WMC is very important to the study of psychology and aging. These changes consist of periventricular and subcortical types, however it is difficult to detect and segment WMC using only intensity-based methods, because their intensity, level IS similar to th~t of the gray matter (GM). In this paper, we propose a new method of segmenting periventricular WMC using K-means clustering and morphological features.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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• pp.25-31
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• 2008

In this paper, we propose a new method that separates background and foreground from stereo images. This method can be improved automatic target tracking system by using disparity map of the stereo vision system and background-separating mask, which can be obtained camera configuration parameters. We use disparity map and camera configuration parameters to separate object from background. Disparity map is made with block matching algorithm from stereo images. A morphology filter is used to compensate disparity error that can be caused by occlusion area. We could obtain a separated object from background when the proposed method was applied to real stereo cameras system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.29-33
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• 1998

In this paper, we propose a hierarchical segmentation method for tracking a semantic video object using a watershed algorithm based on morphological filtering. In the proposed method, each hierarchy consists of three steps: First, markers are extracted on the simplified current frame. Second, region growing by a modified watershed algorithm is performed for segmentation. Finally, the segmented regions are classified into 3 categories, i.e., inside, outside, and uncertain regions according to region probability values, which are acquired by the probability map calculated from a estimated motion field. Then, for the remaining uncertain regions, the above three steps are repeated at lower hierarchies with less simplified frames until every region is decided to a certain region. The proposed algorithm provides prospective results in video sequences such as Miss America, Clair, and Akiyo.

• Fisheries and Aquatic Sciences
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• v.2 no.2
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• pp.129-134
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• 1999

Haloptilus caribbeanensis Park, 1970 (Copepoda, Calanoida, Augaptilidae) is redescribed in detail on the basis of an adult female collected from Suruga Bay, Japan. This is the first record of the species from the Indo-Pacific region. Morphology of the Pacific specimen agrees well with that of the Caribbean Sea and Gulf of Mexico specimens, except for the numbers of mandibular teeth. The former has five teeth and the latter six teeth on mandible. The segmentation and segmental aesthetasc numbers of female antennules of H. caribbeanensis are compared with those of five species of Haloptilus (H. angusticeps, H. fons, H. longicomis, H. ornatus and H. spiniceps). These characters show morphological differentiation at the species level. H. caribbeanensis has no aesthetasc on the proximal segments II, IV, and VI of the female antennules.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.847-850
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• 2004

본 논문에서는 모폴로지(Morphology) 재구성(Reconstruction)과 비선형 확산(Non-Linear Diffusion)을 이용하여 칼라 영상을 유사한 영역으로 분할하는 방법을 제안한다. 초기에 RGB 영상을 LUV 색상 공간으로 전환하고, 그 색상공간에 모폴로지를 응용한 재구성(Reconstruction)에 의한 닫힘(Closing) 연산과 비선형 확산(Non-Linear Diffusion)을 적용하여 잡음을 제거한 실험 영상을 획득한다. 이 영상에서 워터쉐드 알고리즘을 위한 칼라 영상의 기울기(Gradient) 정보를 획득하고, 그 영상에 마커(Marker) 정보를 이용한 워터쉐드(Watershed) 알고리즘을 적용하여 영상을 효과적으로 분할한다. 칼라 영상을 대상으로 한 실험에서 제안 방법이 영상을 효과적으로 분할함을 확인 하였다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.651-654
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• 2000

본 논문에서는 칼라 영역으로 확장된 블록단위 영상분할 알고리듬을 제안한다. 즉, 기존의 휘도 성분을 기반으로 한 블록단위 알고리듬을 HSV 칼라 성분을 기반으로 하는 칼라 영상분할로 확장한다. 기존의 수학적 형태학(mathematical morphology)에 기반한 영상분할기법이나 블록단위 영상분할 기법들이 밝기 정보만을 활용했던 것에 대해 제안된 블록단위 영상분할 기법은 밝기뿐만이 아니라 칼라 성분도 고려하여 영상분할의 정확도를 향상시켰다. 실험의 결과 휘도 성분만을 고려한 영상분할 결과 보다 칼라 성분을 사용한 영상분할의 결과가 더 정확함을 알 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.328-330
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• 2001

컴퓨터 비전을 이용한 자동차 번호판 인식은 자동차에 특별한 장치가 필요없어 비용면에서 유리하다. 자동차 번호판을 인식하기 위해서는 번호판의 영역을 추출한 후 번호판에서 문자와 숫자 영역을 분리하고 그 세그먼트를 신경 회로망 혹은 다른 방법을 통하여 인식한다. 본 논문은 자동차 번호판 위치 검출 방법과 세그멘테이션 방법에 대하여 제안한다. 자동차 번호판 위치 검출을 위하여 모폴로지 기법과 ART2 클러스터링 방법을 이용하였고 검출한 번호판 영역에서 세그멘테이션은 모폴로지 연산을 이용한 이진화와 레이블링을 이용한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.201-204
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• 2001

영상분할이란 영상을 동질성과 연결성을 동시에 만족하는 영역들로 나누는 것으로서 최근 영역기반 부호화 등과 같이 영상을 객체 단위로 처리하고자 하는 응용분야에 필수적인 기술이다. 본 연구에서는 원 영상이 너무 세밀하게 분할되어 있거나 영상에 잡음의 분포를 줄이기 위해서 전처리 작업으로 입력 영상을 양자화 시키고, 양자화된 영상을 형태학적인 필터를 이용하여 에지를 추출함으로서 원 영상을 분할하는 방법을 제안한다.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.75-86
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• 1999

Three dimensional city model is composed of man-made and natural features, among these, most of man-made features are buildings. Therefore, it is very important to extract the building informations accurately and promptly to update the existing database. To achieve this, DTM can be reconstructed using building Information which is extracted from DTM, then this can be used as three dimensional city model. Thus, this paper aims to extract building boundaries and heights from high resolution DTM and edge informations of aerial photograph using mathematical morphology and image segmentation. We found that it is possible to extract buildings using opening operation in mathematical morphology and to improve the accuracy of building extraction using edge informations from aerial photograph.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.430-441
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• 2002

Video object segmentation is an important component for object-based video coding scheme such as MPEG-4. In this paper, a robust algorithm for segmentation of moving objects in video sequences and VOP(Video Object Planes) extraction is presented. The points of this paper are detection, of an accurate object boundary by associating moving object edge with spatial object edge and generation of VOP. The algorithm begins with the difference between two successive frames. And after extracting difference image, the accurate moving object edge is produced by using the Canny algorithm and morphological operation. To enhance extracting performance, we app]y the morphological operation to extract more accurate VOP. To be specific, we apply morphological erosion operation to detect only accurate object edges. And moving object edges between two images are generated by adjusting the size of the edges. This paper presents a robust algorithm implementation for fast moving object detection by extracting accurate object boundaries in video sequences.