• Journal of the Korea Fashion and Costume Design Association
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• v.5 no.3
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• pp.25-36
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• 2003

The purpose of this study is to analyze the expressive technique of grunge look in knitwear fashion. For this study, I have investigated theories of retro and decontructionism trends, and have examined pictures from professional fashion magazines. The results of study on the expressive technique of grunge look reflected on the knitwear fashion were as follows; (1) patchwork technique, which is an outstanding method of recycling, (2) handknitting technique, which came from retro trend of hippism, (3) unfinished edge, which emphasized the image of poverty and incompleteness, (4) irregular lace knitting and slash technique, which is the typical details of grunge look and denies the traditional fashion order, (5) hand stitch technique using various materials, which gives second-hand mood of hippie look, and (6) fringe details, which originated from the unfinished edge technique.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.113-116
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• 2000

Human face recognition and 3D human face reconstruction has been studied in this paper. To find the facial feature points, find edge from input image and analysis the accumulated histogram of edge information. This paper use a Generic Face Model to display the 3D human face model which was implement with OpenGL and generated with 500 polygons. For reality of 3D human face model, we propose Group matching mapping method between facial feature points and the one of Generic Face Model. The personalized 3D human face model which resembles real human face can be generated automatically in less than 5 seconds on Pentium PC.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1903-1906
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• 2003

This paper proposes an adaptive regularized noise smoothing algorithm for range image using the area decreasing flow method, which can preserve meaningful edges during the smoothing process. Although the area decreasing flow method can easily smooth Gaussian noise, it has two problems; ⅰ) it is not easy to remove impulsive noise from observed range data, and ⅱ) it is also difficult to remove noise near edge when the adaptive regularization is used. In the paper, therefore, the second smoothness constraint is addtionally incorporated into the existing regularization algorithm, which minimizes the difference between the median filtered data and the estimated data. As a result, the Proposed algorithm can effectively remove the noise of dense range data with edge preserving.

• 전자공학회논문지 IE
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• v.49 no.1
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• pp.24-29
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• 2012

In this paper, we propose a progressive filter for impulse noise reduction. The proposed method uses non-linear filter and linear filter progressively. Non-linear filter reduces abrupt noise pattern. Also, linear filter adjusts filtering direction according to an edge in the image which is filtered by non-linear filter. Thus, our proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing non-linear and linear progressive filtering methods.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.587-589
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• 1995

The safe navigation of a mobile robot requires the recognition of the environment in terms of vision processing. To be guided in the given path, the robot should acquire the information about where the wall and corridor are located. Also unexpected obstacles should be detected as rapid as possible for the safe obstacle avoidance. In the paper, we assume that the mobile robot should be navigated in the flat surface. In terms of this assumption we simplify the correspondence problem by the free navigation surface and matching features in that coordinate system. Basically, the vision processing system adopts line segment of edge as the feature. The extracted line segments of edge out of both image are matched in the free nevigation surface. According to the matching result, each line segment is labeled by the attributes regarding obstacle and free surface and the 3D shape of obstacle is interpreted. This proposed vision processing method is verified in terms of various simulations and experimentation using real images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.209-213
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• 2010

In this paper, an efficient predictor for entropy coding is proposed. It adaptively selects one of two prediction errors obtained by MED(median edge detector) or GAP(gradient adaptive prediction). The reduced error is encoded by existing entropy coding method. Experimental results show that the proposed algorithm can compress higher than existing predictive methods.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.10
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• pp.28-34
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• 1997

This paper describes an automatic measurement method for the in-line inspection of assembly tolerances of cathod ray electron guns. The method uses an optical microscope with a CCD camera as a probe. An automatic gap recognition algorthm with digital image processing and a new software autofocus algorithm based on using an optimal edge detector have been developed to improve the measuring accuracy. An inspection system has been proposed and practically implemented for in-line inspection to a real factory automation line. The inspection system consists of a gap inspection part and an eyelet. Total time consumed for inspecting all measuring items is about 10 seconds and the repeatability is below .+-. 5 .mu. m

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.2
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• pp.108-120
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• 1989

The paper describes a new algorithm for reducing the edge degradation of a vector quantization(VQ) in low rates. This algorithm exploits several codebooks, one of which is adaptively selected by standard deviation(SD) of the vector currently being coded. Also, SD search method for reducing the complexity of codebook search is proposed. As a result, a proposed VQ has good performance anout 30 dB PSNR in the 0.4-0.7 bpp range.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.148-155
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• 2003

In this paper, a nonlinear anisotropic filtering method without the loss of important information happened due to the repeated filtering in magnetic resonance images is proposed. First of all original images are divided into four regions, e.g., SPR(Strong Plain Region), EPR(Easy Plain Region), SER(Strong Edge Region), and EER(Easy Edge Region). An optimal template among multiple templates is selected, then the nonlinear anisotropic filtering based on the template is applied in pixel by pixel basis. In the proposed algorithm, filtering strength of EER containing important information is adjusted very weak and filtering strength for remaining regions is also adjusted according to the degree of the importance. In spite of repeated filtering, resulting images by the proposed method could still preserve anatomy information of original images without any degradation. Compared to the existing nonlinear anisotropic filtering, the proposed filtering method with multiple templates provides higher reliability for filtered images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.382-393
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• 1991

In this paper, we propose a method for recognizing printed Korean characters using the Preceding Layer Driven multi-layer perceptron. The new learning algorithm which assigns the weight values to an integer and makes use of the transfer function as the step function was presented to design the hardware. We obtained 522 Korean character-image as an experimental object through scanner with 600DPI resolution. The preprocessing for feature extraction of Korean character is the separation of individual character, noise elimination smoothing, thinnig, edge point extraction, branch point extraction, and stroke segmentation. The used feature data are the number of edge points and their shapes, the number of branch points, and the number of strokes with 8 directions.