• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.185-194
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• 1993

In this research, the image obtained by TM platformed in the LANDSAT-5 and the terrestrial infrared image obtained by the Thermo Tracer were employed in order to search the distribution of industrial thermal plume discharged into seas. Sea surface temperature distributions were deduced based on the infrared band 6 in the TM image of the LANDSAT by employing the transformal formula provided by the CSFC of the NASA and post-calibration values. The temperature distributions were also obtained with the processing mode of the TH1100 series from the terrestrial thermal image or the Thermo tracer. According to the results of the image analyses with this methods, it was found that sea surface temperatures in shallow coastal area largely affected by the temperatures of the freshwater and inland and that the range and the area of distribution of the thermal plume can be visualized quantitatively. Furthermore, when the terrestrial thermal infrared scanner is used, the more details of the distribution range can be obtained, and the image results are comparable to those obtained from the LNADSTA.

• Progress in Medical Physics
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• v.14 no.3
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• pp.203-210
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• 2003

PET (positron emission tomography) permits the investigation of physiological and biochemical processes in vivo. The accuracy of quantifying PET data is affected by its finite spatial resolution, which causes partial volume effects. In this study, we developed a method for partial volume correction using Hoffman phantom PET and MR data, and applied various FWHM (full width at half maximum) levels. We also applied this method to PET images of normal controls and tested for the possibility of clinical application. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices. The gray matter and white matter regions were then segmented into binary images. Each binary image was convolved by 4, 8, 12, 16 mm FWHM levels. These convolved images of gray and white matter were merged corresponding to the same level of FWHM. The original PET images were then divided by the convolved binary images voxel-by-voxel. These corrected PET images were multiplied by binary images. The corrected PET images were evaluated by analyzing regions of interests, which were drawn on the gray and white matter regions of the original MR image slices. We calculated the ratio of white to gray matter. We also applied this method to the PET images of normal controls. On analyzing the corrected PET images of Hoffman phantom, the ratios of the corrected images increased more than that of the uncorrected images. With the normal controls, the ratio of the corrected images increased more than that of the uncorrected images. The ratio increase of the corrected PET images was lower than that of the corrected phantom PET images. In conclusion, the method developed for partial volume correction in PET data may be clinically applied, although further study may be required for optimal correction.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.533-535
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• 1999

자궁경부진 세포인식 시스템에 있어서 가장 중요한 것이 영상처리를 이용하여 세포핵과 세포질을 추출하여 세포의 형태적인 정보를 알아내는 과정이다. 기존의 전역 thresholding 기법이나 region growing의 경우는 pap smear 검사를 통해 얻어진 세포 영상을 분할할 수 있는 region growing 기법을 제안한다. 제안된 region growing 기법은 초기에 seed를 검출할 때 local threshold growing 기법을 제안한다. 제안된 region growing 기법은 초기에 seed를 검출할 때 local threshold 개념을 도입하여 seed의 검출을 고르게 하고, 2가지 확장 조건을 사용하여 영역을 확장한다. 첫 번째 확장 조건은 비정상 세포나 artifact가 많아서 어둡게 나타나는 영상이나 세포질과 배경의 경계가 뚜렷하지 않아서 세포질의 구별이 어려운 영상의 영역 분할이 가능하도록 그 특성을 반영하고, 두 번째 조건은 세포가 흡수하는 빛의 양이 일정하다는 가정으로 영상에서의 지역 특성(gray level, color 등을 반영한다. 제안된 기법은 정상세포 영상뿐만 아니라 비정상 세포 영상에 대하여 over-segment나 under-segment하는 경우를 줄여서 영역 분할에 좋은 결과를 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2352-2355
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• 2003

In recent yeas, studies on computer aided diagnosis (CAD) using image analysis on CT images have been conducted with respect to various diseases. Extracting ground-glass opacities (GGO) on lung CT images is one of such subjects, though it has not found an established method yet. If the region of ground-glass opacities is large on CT images, it can be detected without much difficulty. On the other hand, if the region is small, it is still difficult to find it exactly. In the latter case, increasing overlooking possibility cannot be avoided according to smaller size of the region. To solve this difficulty, this paper proposes an automatic technique for extracting ground-glass opacities on lung CT images employing some statistical parameters of a gray level histogram and a differential histogram. The proposed technique is applied to some lung CT images in the performed experiment. The results are shown with discussion on future work.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.111-119
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• 1992

In this paper, we propose an edge detection scheme for noisy images based on the co-occurrence matrix. In the proposed scheme based on the step edge model, the gray level information is simply converted into a bit-map, i.e., the uniform and boundary regions of an image are transformed into a binary pattern by using the local mean. In this binary bit-map pattern, 0 and 1 densely distributed near the boundary region while they are randomly distributed in the uniform region. To detect the boundary region, the co-occurrence matrix on the bit-map is introduced. The effectiveness of the proposed scheme is shown via a quantitative performance comparison to the conventional edge detection methods and the simulation results for noisy images are also presented.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.357-362
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• 2008

The new approach was proposed which uses Shannon function based on variable length in order to detect the edges of image. The proposed casted the detection of edges in images on the space information of the images. In addition the algorithm which measures the possibility of edges was proposed. Lots of simulations showed that the approach in this paper was more good than the conventional methods in detecting meaningful discontinuities in gray level.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.149-160
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• 2001

In this paper we employ two-sample location tests such as Wilcoxon test and T test for detecting edges in noisy images. For this, we compute a test statistic on pixel gray levels obtained using an edge-height parameter and compare it with a threshold determined by a significance level. Experimental results applied to sample images are given and performances of these tests in terms of the objective measure are compared.

• Journal of Biomedical Engineering Research
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• v.13 no.1
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• pp.33-38
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• 1992

A new approach to texture classification for quantitative ultrasound liver diagnosis using run difference matrix was developed. The run difference matrix comprised the gray level difference along with a distances. From this run difference matrix, we defined several vectors and parameters such as DOD, DGD, DAD vector, SHP, SMO, SMG, LDE, LDEL etc. Each parameter values calculated in fatty, cirrhotic, normal and chronic hepatitic liver images were plotted in a plane and we found that RDM method was more sensitive to small structural changes than the conventional run length method and showed improved classification ability between the diseases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.290-300
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• 1995

본 연구는 JPEG(Joint Photographic Experts Group)표준 영상압축 방법을 이용한 원격측정 (remote measuring) 시스템을 다룬다. 많은 디지탈 비디오(digital video)이 응용중에서 주요 어려움은 디지탈 영상(digital image)을 직접적으로 표현하기 위해 필요한 방대한 데이터의 처리문제이다. 그리고 디지탈 영상의 직접적인 사용은 고수준 기억용량(high storage)과 전송비용(transmission costs)으로 인하여 응용상 여러가지 제약조건이 수반되었다. 이런 이유로 인하여 여러가지 영상압축 기법이 개발되어왔으며 본 연구는 정지영상(still pictures)에 대하여 JPEG 표준을 사용한 영상압축과 압축된 영상을 사용하여 실제 제조업의 공정검사에 응용하는 것이다. 수행도 평가척도로서 원래영상과 압축된 영상과의 압축비, 원래영상과 압축된 영상과의 픽셀(pixel)의 회색도 값(gray-level value)의 평균과 RMSE(root mean square error), 그리고 원래영상과 압축된 영상을 원거리(또는 근거리)로 전송하여 전송된 압축영상을 푼 후 두 지점간의 거리 측정에 따르는 실제거리와 측정거리에 대한 오차를 이용하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.248-253
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• 1998

만화 제작에 있어 시나리오 뿐 만 아니라 등장 인물(캐릭터)의 개발이 중요한 부분을 차지하고 있으므로 새로운 캐릭터 창작을 쉽게 개발하기 위한 방법의 일환으로 기존 인물 영상의 특징을 초대한 고려한 윤곽선을 추출하여 이를 캐릭터 개발에 활용할 수 도 있을 것이다. 이런 목적으로 지금까지 영상의 윤곽선 추출방법들이 많이 제안되었으나 대부분은 그레이 레벨 영상을 이진 영상으로 변환한 후 윤곽선을 추출하는 과정에서 정보의 손실이 발생할 수도 있으며 불필요한 잡영이 추가될 수 있었다. 본 논문은 이런 단점을 보완하기 위해 그레이 레벨 영상에서 직접 윤곽선을 추출하려는 시도로서, 전처리 과정에서는 local averaging으로 잡영을 줄인 후 Prewitt 연산자를 이용하여 에지를 검출하고, 윤곽선 추출에 적합하도록 기존의 지형적 특징 할당 방법을 수정하여 적용한 중간 결과에 대해 직선화 과정으로 잡음들을 제거하여 최종 윤곽선을 구한다.