• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.9-15
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• 2012

In this paper, we propose a method to segment a color image into several meaningful regions. We suppose that the meaningful region has a set of colors with high frequency in the color image. To find these colors, the color image is represented as several sets of color points in RGB space. And when we use the density of points defined in this method, color belonging to a dense region of color points in RGB space refers to the color that appeared frequently in the image. Eventually, we can find meaningful regions by looking for regions with high density of color points using our level set function in RGB space. However, if a meaningful region does not have a contiguous region of the sufficient size in the image, this is not a meaningful region but meaningless region. Thus, the pixels in the meaningless region are assigned to the biggest meaningful region belonging to its neighboring pixels in the color image. Our method divides the color image into meaningful regions by applying the density of color points to level set function in RGB space. This is different from the existing level set method that is defined only in 2D image.

• Journal of the Korea Computer Graphics Society
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• v.15 no.3
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• pp.19-26
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• 2009

In this paper, a new adaptive vertex clustering using a KD-tree is presented for 3D mesh partitioning. A vertex clustering is used to divide a huge 3D mesh into several partitions for various mesh processing. An octree-based clustering and K-means clustering are currently leading techniques. However, the octree-based methods practice uniform space divisions and so each partitioned mesh has non-uniformly distributed number of vertices and the difference in its size. The K-means clustering produces uniformly partitioned meshes but takes much time due to many repetitions and optimizations. Therefore, we propose to use a KD-tree to efficiently partition meshes with uniform number of vertices. The bounding box region of the given mesh is adaptively subdivided according to the number of vertices included and dynamically determined axis. As a result, the partitioned meshes have a property of compactness with uniformly distributed vertices.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.25-33
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• 2001

본 연구는 무감독 영상 분류를 위하여 지역 확장 영상 분할과 계층 연결 영상 분류를 포함하는 다중 단계 기법을 제안하고 있다. 모의 자료를 사용하여 제안된 알고리듬 대한 평가와 효율성에 대한 검증을 하였다.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1484-1486
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• 2015

그리드 기반 공간 분할 방식에서 셀 크기는 성능을 좌우하는 핵심 요소이다. 본 논문에서는 각 셀에서 충돌 검사가 일어나는 빈도에 따라 동적으로 셀의 크기를 제어하는 방식을 제안한다. 각 셀의 충돌 검사 빈도와 인접한 셀과 병합했을 때의 충돌 검사 빈도를 비교하여, 이 차이가 임의의 값보다 작을 때 셀들을 병합하여 하나의 큰 셀로 만든다. 단, 병합할 셀이 여러 개일 경우 충돌 검사 빈도가 작은 셀부터 차례로 병합한다. 이 방식을 통하여 셀의 수 및 업데이트 비용을 줄일 수 있으며 이는 공간상의 객체가 규칙적인 움직임을 보일 때 가장 효율적임을 확인했다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.99-105
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• 2011

In this paper, we proposed a method for estimating an accurate gamut based on segment maxima method. According to the number of segments in the segment maxima, a local concavity is generated in the vicinity of lightness axis or a gamut is reduced in high chroma region. It induces artifacts or deterioration of the image quality. To remove these artifacts, the number of segment is determined according to the number of samples. and a local concavity is modified by extending a detected concave point to the line connecting two adjacent boundary points. Experimental results show that the contours in a uniform color region and speckle artifacts from the conventional segment maxima algorithm are removed.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.320-322
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• 2012

코 내부의 복잡한 기하학적 형상으로 인해 nasal airway의 분리는 많은 어려움을 겪고 있다. 본 논문은 velocimetry of nasal airflow 와 코 수술 계획을 위하여 3차원 공간에서 nasal airway를 interactive semiautomatic으로 분리하고 시각화하는 방법을 제안한다. 제안하는 방법은 ROI(Region-Of-Interest)와 multi-seed 3d region growing(MS3RG)기법을 적용하여 비강을 분리하며 볼륨렌더링 기법을 이용하여 분리된 영역을 3차원 공간에서 직관적으로 확인 할 수 있다. 또한 분리된 3차원 비강 모델은 유동흐름 실험을 위하여 3차원 프린터를 통해 실제 모형으로 제작 가능하다. 그리하여 CT dataset(512*512*175)을 가지고 매뉴얼 세그멘테이션에서 5시간 정도 걸리던 작업을 반자동 세그멘테이션 방법을 이용할 경우 최대 3분 이내에 분리 작업을 완료할 수 있으며 수치해석 실험 및 물리 실험에 이용할 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.90-98
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• 2011

The recognition and classification of paddy rice disease are of major importance to the technical and economical aspect of agricultural industry over the world. Computer vision techniques are used to diagnose rice diseases and to efficiently manage crops. Segmentation of lesions is the most important technique to detect paddy rice disease early and accurately. A new Gaussian Mean (GM) method was proposed to segment paddy rice diseases in various color spaces. Different color spaces produced different results in segmenting paddy diseases. Thus, this empirical study was conducted with the motivation to determine which color space is best for segmentation of rice disease. It included five color spaces; NTSC, CIE, YCbCr, HSV and the normalized RGB(NRGB). The results showed that YCbCr was the best color space for optimal segmentation of the disease lesions with 98.0% of accuracy. Furthermore, the proposed method demonstrated that diseases lesions of paddy rice can be segmented automatically and robustly.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.21-29
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• 2019

This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.535-544
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• 2018

As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

• Journal of KIISE:Databases
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• v.28 no.1
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• pp.69-85
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• 2001

공간 데이터베이스에서 효율적으로 공간 질의를 처리하기 위해서는 클러스터링을 통해서 이스크 접근 비용을 줄이는 것이 필요하다. 이 논문은 공간 지역성에 기반을 둔 여러 가지 클러스터링 알고리즘을 제안하고 실험을 통해 제안한 클러스터링 알고리즘의 성능을 평가하였다. 이 논문에서 제안하는 클러스터링 알고리즘은 객체 클러스터링 알고리즘과 셀 클러스터링 알고리즘으로 나뉜다. 객체 클러스터링 알고리즘은 정규 준할 공간 색인 구조에서 영역 분할 선과 겹치는 객체들의 저장 위치를 결정하는데 사용된다. 셀 클러스터링 알고리즘은 클러스터를 만들기 위해 정규 분할된 영역들을 그룹화하는데 사용된다. 실험결과 객체 클러스터링 알고리즘에서는 객체간의 거리를 이용한 경우에 대체로 좋은 성능을 보였지만, 버퍼 크기가 커지거나 데이터가 희박한 영역의 질의에 있어서는 알고리즘 별로 성능의 차이는 거의 없었다. 셀 클러스터링 알고리즘에 대한 실험에서는 이 논문에서 제안한 클러스터링 알고리즘은 N-순서화 기법에 의한 클러스터링 알고리즘에 비해 우수한 성능을 보였다. 특히 중복 참조도를 이용한 경우와 셀의 무게 중심간 거리를 이용한 방법이 가장 우수하였다.