• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2715-2717
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• 2002

Image segmentation is an essential technique of image analysis. In spite of the issues in contour initialization and boundary concavities, active contour models(snakes) are popular and successful methods for the segmentation. In this paper, we present a new active contour model, GGF snake, for segmentation of endoscopic image. The GGF snake is less sensitive to contour initialization and ensures high accuracy, large capture range, and fast CPU time for computing external force. It was observed that the GGF snake produced more reasonable results in various image types, such as simple synthetic images, commercial digital camera images, and endoscopic images than previous snakes did.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.3
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• pp.1-14
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• 2010

Areas with negative images in cities can degrade the image of the city as a whole and slow the city's efforts to improve its image. The identification of such areas and the development of a city contour that charts the images of various areas in advance can help urban planners establish relevant strategies to ameliorate detrimental images of the city. This study intends to draw a contour of Seongnam City according to citizen's cognition levels of and preference for city area images and aim to shift the strategy of urban image planning from being results-oriented to being process-oriented. The results of this study are as follows: First, an analysis of the level of cognition of and preferences for Seongnam City's landmarks shows that the degree of cognition varies in different areas, whereas that of preferences remains similar; Second, the cognition and preference contour makes it easy to assess and diagnose city images; Third, the image management map, which merges the cognition contour with the preference contour, divides the city into four different areas. In order to manage city images, it follows that those areas with a high degree of cognition but low preference need to be classified and dealt with first. Further, this study shows that those areas with high cognition are the most populated and visited. Areas with high preference can become a strong candidate for being a landscape control point of a city, which adds to the usefulness of this study. The contour of Seongnam will contribute to networking sightseeing areas for visitors centered upon those places of high preference. It would appear that this type of networking will inspire a better image for the city.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.238-245
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• 2001

This paper describes a method for detecting a close leading vehicle using the contour of the vehi-cles rear wheels. The contour of a leading vehicles rear wheels in 속 front road image from a B/W CCD camera mounted on the central front bumper of the vehicle, has vertical components and can be discerned clearly in contrast to the road surface. After extracting positive edges and negative edges using the Sobel op-erator in the raw image, every point that can be recognized as a feature of the contour of the leading vehicle wheel is determined. This process can detect the presence of a close leading vehicle, and it is also possible to calculate the distance to the leading vehicle and the lateral deviation angle. This method might be useful for developing and LSA (Low Speed Automation) system that can relieve drivers stress in the stop-and-go traffic conditions encoun-tered on urban roads.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.934-936
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• 1995

To get a good result of the feature-based stereo matching, contour of buildings must be extracted exactly. In this paper, an algorithm that extracts contour of flat top buildings exactly is proposed. The Algorithm is composed of three steps. One is to find corner points of 4 types in whole image and another is to extract exact lines between coners by edge following technique, the third is to extract exact contour of buildings using binding structures. We have a good result in extracting contour of buildings.

• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.23-28
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• 2003

This paper describes, in order to extract contour from topographic map image, an adaptive segment-length thresholding using a threshold depended on target image. First of all, after recognizing the primary symbols and detecting two edges from the projection histogram of the elevation value area, the threshold value is determined by the distance between the edges. Then, the subdivision is peformed by searching a branch point and erasing its neighboring Hack pixels. And contour components are extracted by segment-length thresholding. The experimental result shows that the final image contains non-contour component of 2.41% and contour one of 97.59%.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1987.10a
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• pp.3-6
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• 1987

• International Journal of Contents
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• v.3 no.4
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• pp.15-21
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• 2007

Image morphing deals with the metamorphosis of one image into another. The field morphing depends on the manual work for most of the process, where a user has to designate the control lines. It takes time and requires skills to have fine quality results. It is an object of this paper to propose a method capable of realizing the semi-automation of field morphing using adaptive vertex correspondence based on image segmentation. The adaptive vertex correspondence process efficiently generates a pair of control lines by adaptively selecting reference partial contours based on the number of vertices that are included in the partial contour of the source morphing object and in the partial contour of the destination morphing object, in the pair of the partial contour designated by external control points through user input. The proposed method generates visually fluid morphs and warps with an easy-to-use interface. According to the proposed method, a user can shorten the time to set control lines and even an unskilled user can obtain natural morphing results as he or she designates a small number of external control points.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.597-605
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• 1999

In this paper, we propose a cardioangiography sequence image coding scheme which use a subtraction between initial image and current frame inserted contrast dye. Stable regions are obtained by the multithreshold and meaningful region is extracted by the images with stable region. The image with meaningful region is classified into contour and texture information. Contour information is coded by contour coding. And texture information is approximated by two-dimensional polynomial function and each coefficients is coded. Experimental results confirm that the sequence of cardioangiography are well reconstructed at the low bit rate (0.02∼0.04 bpp) and high compression ratio.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.549-555
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• 2007

In order to study cortical properties in human, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Among many approaches, surface-based method that reconstructs a 3-D model from contour lines on cross-section images is widely used. In general, however, medical brain imaging has some problems such as the complexity of the images, non-linear gain artifacts and so on. Due these limitations, therefore, extracting anatomical structures from imaging data is very a complicated and time-consuming task. In this paper, we present an improved method for extracting contour lines of cortical surface from magnetic resonance images that simplifies procedures of a conventional method. The conventional method obtains contour lines through thinning and chain code process. On the other hand, the proposed method can extract contour lines from comparison between boundary data and labeling image without supplementary processes. The usefulness of the proposed method has been verified using brain image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.179-184
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• 2004

This paper presents an image segmentation algorithm to obtain the 3D body shape data that the grid pattern and the body contour lute in the background image are extracted using the new proposed hybrid method. The body contour line is extracted based on maximum biased anisotropic recognition(MaxBAR) algorithm which recognizes the most strong and robust edges in the image since the normal derivative at the edges is large, while the tangential derivatives can be small. The grid patterns within body contour lines are extracted by grid pattern detection (GPD). The body contour lilies and the grid patterns are combined. The consecutive run test based on heuristic method is used to link the disconnected line and reduce noise line. This proposed segmentation method is more effective than the conventional method which uses a gradient and a laplacian operator, verified with application two conventional method.