• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.193-200
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• 2009

Recently, there have been efforts to construct hybrids among the existing methodologies for multiphase flow such as VOF, Level Set, and Front Tracking with the intention of facilitating simulations of general three-dimensional problems. As one of the hybrid method, we have developed the Level Contour Reconstruction Method (LCRM) for general three-dimensional multiphase flows including phase change. The main idea was focused on simplicity and a robust algorithm especially for the three-dimensional case. It combines characteristics of both Front Tracking and Level Set methods. While retaining an explicitly tracked interface using interfacial elements, the calculation of a vector distance function plays a crucial role in the periodic reconstruction of the interface elements in the LCRM method to maintain excellent mass conservation and interface fidelity. In addition, compact curvature formulation is incorporated for the calculation of the surface tension force thereby reducing parasitic currents to a negligible level.

• IE interfaces
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• v.9 no.2
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• pp.119-128
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• 1996

A procedure is presented for a 3D-contour machining without cutter interferences. The 3D-contouring machining along a spatial curve is often required for manufacturing trimming and flange dies in motor industries. Input data for the machining contour is a spline curve with polynomial vector equation provided by CATIA system. Points are sampled on the contour curve and line segments and helical curves are approximated from the point data. Cutter interference is checked on the approximated spline and all of interference curves are substituted with interference-free helical curves for a tool path generation. The non-machined curve areas are locally machined by tools with smaller diameters. A tool radius offset is considered for generating NC data to be free with tool size.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.57.4-57
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• 2002

$\textbullet$ Image segmentation is an essential technique of image analysis. In spite of the traditional issues in contour initialization and boundary concavities, active contour models(snakes) are popular and known as successful methods for segmentation. $\textbullet$ We could find in experiment that snake using Gaussian External Force is fast in time but low in accuracy and snake using Gradient Vector Flow by Chenyang Xu and Jerry L. Prince is high in accuracy but slow in time. $\textbullet$ In this paper, we presented a new active contour model, GGF snake, for segmentation of endoscopic image. Proposed GGF snake made up for the defects of the traditional snakes in contour initialization and boundary...

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.593-598
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• 2014

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.414-417
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• 1997

This paper presents vessel contour for extracting features and segmentating narrow blood vessels down to a diameter of two pixels in digital subtraction angiographic image. We present a new tracking algorithm for contour, mainly blood vessels in DSA image, and extracting properties such as their intensities, diameters, and center lines by exploiting spatial continuity. The proposed algorithm comes to detect blood vessel's boundary using difference edge detector one of homogeneity operator and find a next centerline position by direction vector of edge information. This algorithm enhanced variation of vessel's diameter compared to Sun's tracking algorithm and lessoned to compute as direction vector decide adaptively entire vessel's direction field. The processed images are intended to support radiologists in diagnosis, radiation therapy planning, and surgical planning. The algorithm should be useful for automating angiographic analyses of blood vessels.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1889-1891
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• 2004

The differential white blood cell count plays an important role in the diagnosis of different diseases. It is a tedious task to count these classes of cell manually. An automatic counter using computer vision helps to perform this medical test rapidly and accurately. Most commercial-available automatic white blood cell analysis composed mainly 3 steps including segmentation, feature extraction and classification. In this paper we concentrate on the first step in automatic white-blood-cell analysis by proposing a segmentation scheme that utilizes a benefit of active contour. Specifically, the binary image is obtained by thresolding of the input blood smear image. The initial shape of active is then placed roughly inside the white blood cell and allowed to grow to fit the shape of individual white blood cell. The white blood cell is then separated using the extracted contour. The force that drives the active contour is the combination of gradient vector flow force and balloon force. Our purposed technique can handle very promising to separate the remaining red blood cells.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.62-76
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• 1994

In this paper, a segmentation-based coding technique as applied to video sequences is proposed. A proposed method separates an image into contour and texture parts, then the visually-sensitive contour part is represented by chain codes and the visually-insensitive texture part is reconstructed by a representative motion vector of a region and mean of the segmented frame difference. It uses a change detector to find moving areas and adopts variable blocks to represent different motions correctly. For better quality of reconstructed images, the displaced frame difference between the original image and the motion compensated image reconstructed by the representative motion vector is segmented. Computer simulation with several video sequences shows that the proposed method gives better performance than the conventional ones in terms of the peak signal to noise ratio(PSNR) and compression ration.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.540-553
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• 2023

The hollow letter CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is an optimized version of solid CAPTCHA, specifically designed to weaken characteristic information and increase the difficulty of machine recognition. Although convolutional neural networks can solve CAPTCHA in a single step, a good attack result heavily relies on sufficient training data. To address this challenge, we propose a seed filling algorithm that converts hollow characters to solid ones after contour line restoration and applies three rounds of detection to remove noise background by eliminating noise blocks. Subsequently, we utilize a support vector machine to construct a feature vector for recognition. Security analysis and experiments show the effectiveness of this algorithm during the pre-processing stage, providing favorable conditions for subsequent recognition tasks and enhancing the accuracy of recognition for hollow CAPTCHA.

• Journal of Ocean Engineering and Technology
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• v.13 no.1 s.31
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• pp.105-112
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• 1999

This research is an experimental investigation of the region of the Biased Flow. This experiment was carried out in a circulating water channel, and the results are analyzed by using the PIV technique. The results are presented in velocity vector field, velocity contour and vorticity contour. The results were compared with those of Zdravkovich which were carried out in a wind tunnel. These results will be very useful to verify numerical codes.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.10-19
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• 2008

In this paper, we propose an automated silhouette extraction method that can effectively extract inner-patterns and silhouettes from 3D scan data of cultural asset. First of all, after creating the edge list of 3D vector data, we decide contour edge and crease edge according to viewpoint. In the next step, after extracting surface silhouette by investigating the vector variation of adjacent faces in crease edge, we finally extract the contour silhouette and surface silhouette for generating the blueprint of cultural asset. To evaluate the performance of the proposed silhouette extraction method, we performed experiments of silhouette extraction using a traditional tile model, a car model and a stone monument model. Comparing with the conventional threshold-based silhouette extraction method, the proposed method extracted more distinct and clear surface silhouettes and inner-patterns by effectively removing meaningless edges, such as noise.