• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.457-467
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• 2000

In this paper, we propose the method to extract the anatomical objects in medical images using active contour models and genetic algorithms. The performance of active contour models is mostly decided by the optimization of active contour model's energy. So, we propose to use genetic algorithms to optimize the energy of active contour models. We experimented our proposed method on the femoral head medical images and proved that our method provides very acceptable results from any initialization of active contour models.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.158-166
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• 2002

In this paper, we proposed a contour shape description method which use the CFR(contour fluctuation ratio) feature. The CFR is the ratio of the line length to the curve length of a contour segment. The line length means the distance of two end points on a contour segment, and the curve length means the sum of distance of all adjacent two points on a contour segment. We should acquire rotation and scale invariant contour segments because each CFR is computed from contour segments. By using the interleaved contour segment of which length is proportion to the entire contour length and which is generated from all the points on contour, we could acquire rotation and scale invariant contour segments. The CFR can describes the local or global feature of contour shape according to the unit length of contour segment. Therefore we describe the shape of objects with the feature vector which represents the distribution of CFRs, and calculate the similarity by comparing the feature vector of corresponding unit length segments. We implemented the proposed method and experimented with rotated and scaled 165 fish images of fifteen types. The experimental result shows that the proposed method is not only invariant to rotation and scale but also superior to NCCH and TRP method in the clustering power.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.740-747
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• 2017

A fast cell contour extraction method using CUDA parallel processing technique is presented. The cell contour extraction is one of important processes to analyze cell information in pathology. However, conventional sequential contour extraction methods are slow for a huge high-resolution medical image, so they are not adequate to use in the field. We developed a parallel morphology operation algorithm to extract cell contour more quickly. The algorithm can create an inner contour and fail to extract the contour from the concave part of the cell. We solved these problems by subdividing the contour extraction process into four steps: morphology operation, labeling, positioning and contour extraction. Experimental results show that the proposed method is four times faster than the conventional one.

• Journal of Periodontal and Implant Science
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• v.29 no.1
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• pp.117-130
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• 1999

All contours of the restoration not directly related to occlusion are related to the gingival tissues only.And proper contour of restoration is essential for the health of the periodontal tissues.But there are so many controversies about the contour of the restoration, and there is no uniform agreement in the literature as to which contour of restoration is best for periodontium. In general, the contour of restoration means the supragingival contour only but in the case of the intracrevicular restorative procedure the subgingival contour of restoration must be considered. Because a portion of the restoration is placed in a gingival sulcus which is extremely vulnerable to periodontal disease. In this article the concepts or theories of the supragingival contour, the subgingival contour, and the emergence profile were discussed.The contour of the restoration and the biotype of the periodontium must be considered in intracrevicular restorative procedure.And sufficient tooth preparation is important factor to develop the proper contour of restoration which is kind to periodontium.

• 한국기계연구소 소보
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• s.20
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• pp.13-20
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• 1990

An algorithm is presented for 3-dimensional contour lines with a hidden line removal ~technique developed by T.L. Janssen(l). Contour line algorithm on any 3-dimensional plane cutting solid body is also shown. NUFIG(2) algorithm is adopted for searching contour lines. Test problems show well-established contour lines on the surface and also on the cutting plane of the structure.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.915-918
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• 1998

Region based coding consistsof image segmentation contour and texture coding. Contour coding techniques can be classified into contour or shape-oriented approaches. In this paper, geodesic skeleton based on shape-oriented approach is used for contour coding. Efficient application of geodesic skeleton for contour coding based on the characteristics of regions in segmented image will be discussed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.5
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• pp.100-105
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• 2002

The comprehensive system analysis for contour milling operation and its error has performed in this study. The obtained experimental results were from the practical points of view. In down-milling operation the contour error curve illustrates bigger thean actual workpiece radius. The contour error increased when the cutter loads increased. Through the procedural evaluation, it could ascertain the characteristics of generation mechanics in circular contour machining error, and the weight of each factors.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.100-106
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• 2004

In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.64-71
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• 2004

The growing need for higher precision and productivity in manufacturing industry has lead to an increased interest in computer numerical control (CNC) systems. It is well known fact that the cross-coupling controller (CCC) is an effective method for contouring applications. In this paper, a multi-axis contour error controller (CEC) based on a contour error vector using parametric curve interpolator is introduced. The contour error vector is a vector from the actual tool position to the nearest point on the desired path. The contour error vector is the closest error model to the contour error. The simulation results show that the CEC is more accurate than the conventional CCC for a biaxial motion system. In addition, the experimental results on 3-axis motion system show that the CEC is simply applied to 3-axis motions and contouring accuracy is significantly improved.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1180-1188
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• 2015

In this paper, a parallel cell contour line extraction algorithm using CUDA, which has no inner contour lines, is proposed. The contour of a cell is very important in a cell image analysis. It could be obtained by a conventional serial contour tracing algorithm or parallel morphology operation. However, the cell image has various damages in acquisition or dyeing process. They could be turn into several inner contours, which make a cell image analysis difficult. The proposed algorithm introduces a min-max coordinates table into each CUDA thread block, and removes the inner contour in parallel. It is 4.1 to 7.6 times faster than a conventional serial contour tracing algorithm.