• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.204-207
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• 2003

실시간으로 배경에서 분리된 정확한 얼굴 영역을 찾아내는 것은 인식의 가장 기본적인 선행과제이다 얼굴을 찾기 위한 방법 중에 특징기반의 모서리(edge) 정보의 추출과 ellipse fitting 알고리즘을 이용하여 배경으로부터 얼굴을 효과적으로 분리해낸다. 얼굴인식을 하기 위한 얼굴 데이터베이스를 선처리 되어진 배경과 분리된 영상이 검출 된다.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.215-219
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• 2015

Cells in a culture process transform with time and produce many overlapping cells in their vicinity. We are interested in a separation algorithm for images of overlapping cells taken using a fluorescence optical microscope system during a cell culture process. In this study, all cells are assumed to have an ellipse-like shape. For an ellipse fitting-based method, an improved least squares method is used by decomposing the design matrix into quadratic and linear parts for the separation of overlapping cells. Through various experiments, the improved least squares method (numerically stable direct least squares fitting [NSDLSF]) is compared with the conventional least squares method (direct least squares fitting [DLSF]). The results reveal that NSDLSF has a successful separation ratio with an average accuracy of 95% for two overlapping cells, an average accuracy of 91% for three overlapping cells, and about 82% accuracy for four overlapping cells.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.73-77
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• 2012

This paper reports a combined depth- and model-based face detection and tracking approach. The proposed algorithm consists of four functional modules; i) color-based candidate region extraction, ii) generation of the depth histogram for handling occlusion, iii) rotation-invariant face region detection using ellipse fitting, and iv) face tracking based on motion prediction. This technique solved the occlusion problem under complicated environment by detecting the face candidate region based on the depth-based histogram and skin colors. The angle of rotation was estimated by the ellipse fitting method in the detected candidate regions. The face region was finally determined by inversely rotating the candidate regions by the estimated angle using Haar-like features that were robustly trained robustly by the frontal face.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.43-48
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• 2008

This paper proposes a new method for measuring the power of spherical and cylindrical lens with 6 points light source, which is composed of a LED and six holes, and magnification ellipse fitting algorithm. Each measured diagonal length of 6 points light source is determined by the target lens power. After finding the center position of each light point with threshold method, 3 axis-diagonal lengths were calculated. The long axis and short axis power of cylindrical lens can be calculated by using magnification ellipse fitting algorithm with the magnification relationships between the initial diagonal lengths and the measured diagonal lengths changed by lens power.

• Communications of the Korean Mathematical Society
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• v.17 no.1
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• pp.121-142
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• 2002

We are interested in the curve fitting problems in such a way that the sum of the squares of the orthogonal distances to the given data points is minimized. Especially, the fitting an ellipse to the given data points is a problem that arises in many application areas, e.g. computer graphics, coordinate metrology, etc. In [1] the problem of fitting ellipses was considered and numerically solved with general purpose methods. In this paper we present another new ellipse fitting algorithm. Our algorithm if mainly based on the steepest descent procedure with the view of ensuring the convergence of the corresponding quadratic function Q(u) to a local minimum. Numerical examples are given.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.28-35
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• 2021

In this study, an image processing method for the measurement of two-phase bubbly flow is developed. Shadowgraphy images obtained by high-speed camera are used for analysis. Some bubbles are generated as single unit and others are overlapped or clustered. Single bubbles can be easily analyzed using parameters such as bubble shape, centroid, and area. But overlapped bubbles are difficult to transform clustered bubbles into segmented bubbles. Several approaches were proposed for the bubble segmentation such as Hough transform, connection point method and watershed. These methods are not enough for bubble segmentation. In order to obtain the size distribution of bubbles, we present a method of splitting overlapping bubbles using watershed and approximating them to ellipse. There is only 5% error difference between manual and automatic analysis. Furthermore, the error can be reduced down to 1.2% when a correction factor is used. The ellipse fitting algorithm developed in this study can be used to measure bubble parameters accurately by reflecting the shape of the bubbles.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2124-2127
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• 2003

This paper suggests user interface method with wearable computer by means of detecting gaze under HMD, head mounted display, environment. System is derived as follows; firstly, calibrate a camera in HMD, which determines geometrical relationship between monitor and captured image. Second, detect the center of pupil using ellipse fitting algorithm and represent a gazing position on the computer screen. If user blinks or stares at a certain position for a while, message is sent to wearable computer. Experimental results show ellipse fitting is robust against glint effects, and detecting error was 6.5％, and 4.25％ in vertical and horizontal direction, respectively.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.40.1-40.1
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• 2014

We have classified barred galaxies for 418 RC3 sample galaxies within z < 0.01 from SDSS DR7 using the visual inspection, ellipse fitting method and Fourier analysis. We found the bar fraction to be ~60%, 43% and 70% for each method and that the ellipse fitting method tends to miss the bar when a large bulge hides the transition from bar to disk in early spirals. We also confirmed that the Fourier analysis cannot distinguish between a bar and spiral arm structure. These systematic difficulties may have produced the long-time controversy about bar fraction dependence on Hubble sequence, mass and color. We designed a new method to fine bars by analyzing the ratio map of bar strength in polar coordinates, which yields the bar fraction of ~27% and ~32% for SAB and SB, respectively. The consistency with visual inspection reaches around 70%, and roughly 90% of visual strong bar are classified as SAB and SB in our classification. Although our method also has a weakness that a large bulge lowers the value of bar strength, the missing bar fraction in early spirals is reduced to the level of ~1/4 compared to the ellipse fitting method. Our method can make up for the demerits of the previous automatic classifications and provide a quantitative bar classification that agrees with visual classification.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1472-1475
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• 1999

This paper proposes a new detection method of human faces in grey scale images with cluttered background using a facial template and elliptical structure of the human head. Face detection technique can be applied in many areas of image processing such as face recognition, composition and computer graphics, etc. Until now, many researches about face detection have been done, and applications in more complicated conditions are increasing. The existing technique proposed by Sirohey shows relatively good performance in image with cluttered background, but can apply only to image with one face and needs much computation time. The proposed method is designed to reduce complexity and be applied even in the image with several faces by introducing template matching as preprocess. The results show that the proposed method produces more correct detection rate and needs less computation time than the existing one.