• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2001년도 제34회 추계학술대회 개최
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• pp.53-58
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• 2001

Fractal dimension is the method to measure the roughness and the irregularity of something that cannot be defined obviously by Euclidean dimension. And the analysis method of this dimension don't need perfect, accurate boundary and color like analysis lot diameter, perimeter, aspect or reflectivity of wear particles or surface. If we arranged the morphological characteristic of various wear particle by using the characteristic of fractal dimension, it might be very efficient to the diagnosis of driving condition. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are boundary fractal dimension and surface fractal dimension.

• 반도체디스플레이기술학회지
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• 제7권4호
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• pp.13-18
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• 2008

This paper explores a content-based image retrieval framework with relevance feedback based on genetic algorithm (GA). This framework adopts GA to learn the user preferences using the similarity functions defined for all available descriptors. The objective of the GA-based learning methods is to learn the user preferences using the similarity functions and to find a descriptor combination function that best represents the user perception. Experiments were performed to validate the proposed frameworks. The experiments employed the natural image databases and color and texture descriptors to represent the content of database images. The proposed frameworks were compared with the other two relevance feedback methods regarding effectiveness in image retrieval tasks. Experiment results demonstrate the superiority of the proposed method.

• 대한의용생체공학회:의공학회지
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• 제18권1호
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• pp.9-16
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• 1997

We develop an automatic imaging matching technique for combining portal image and simulator image for improvements in localization of treatment in radiation therapy. Fusion of images from two imaging modalities is treated as follows. We archive images thxough a frame-yabber. The simulator and portal images are edge detected and enhanced with interpolated adaptive histouam equalization and combined using geometrical parameters relating the coordinates of two image data sets which are calculated using Fourier descriptors. We don't use any kind of imaging markers for patient's convenience. clinical use of this image matching technique for treatment planning will result in improvements in localization of treatment volumes and critical structures. These improvements will allow greater sparing of normal tissues and more precise delivery of energy to the desired irradiation volume.

• 대한화학회지
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• 제37권1호
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• pp.68-75
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• 1993

분자구조를 기술하는 molecular connectivity index, Wiener index 및 ad hoc descriptor와 알코올, 에스테르, 케톤 화합물들이 생체내에서 나타내는 enzyme inhibitory potency, lipoxygenase inhibition, tadpole narcosis potency, 증기독성(vapor toxicity), 증발열(heat of vaporization)과 같은 성질들 사이의 상관관계를 조사하였다. 생물학적 활성의 종류에 따라 molecular descriptor 사이의 우열은 있으나, 대체로 좋은 상관관계식을 얻었다.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권7호
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• pp.453-457
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• 2005

With the expansion of Internet, a variety of image databases are widely used and it is needed to select the part of an image what he wants. In contents-based image retrieval system, Zernikie moment and ART Descriptors are used fur shape descriptors in MPEC-7. This paper presents a fast computation method to determine the radius of a bounding circle that encloses an object in a binary image. With conventional methods, the whole area of the image should be scanned first and the distance from every pixel to the center point be computed. The proposed 4-directional scan method and fast circle-drawing algorithm is utilized to minimize the scanning area and reduce the number of operations fur computing the distance. Experimental results show that proposed method saves the computation time to determine the radius of a bounding circle efficiently.

• Journal of Information Processing Systems
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• 제11권4호
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• pp.643-654
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• 2015

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2000년도 제32회 추계학술대회 정기총회
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• pp.23-28
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• 2000

The determination of surface morphology is believed to be extremely important in the areas of contact mechanics, adhesion and friction. In order to describe morphology of various rubbed surface, the wear test was carried out under different experimental conditions in lubricating wear. And fractal descriptors was applied to rubbed surface of hydraulic driving material with image processing system. These descriptors to analyze surface structure are fractal dimension. Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Morphology of rubbed surface can be effectively obtained by fractal dimensions.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2001년도 제33회 춘계학술대회 개최
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• pp.30-35
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• 2001

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried oui under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are share fractal dimension and surface fractal dimension. The boundry fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined b)r sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2000년도 제32회 추계학술대회 정기총회
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• pp.289-297
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• 2000

The determination of surface topography is believed to be extremely important in the areas of contact mechanics, adhesion and friction. In order to describe topography of various frictional surface, the harding test was carried out under different experimental conditions in try friction. And fractal descriptors was applied to frictional surface of laser modified steel with image processing system These descriptors to analyze surface structure are fractal dimension. Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Topography of frictional surface can be effectively obtained by fractal dimensions.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 춘계학술발표대회
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• pp.781-784
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• 2014

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we use Affine SIFT to detect affine invariant local descriptors for face recognition under large viewpoint change. Affine SIFT is an extension of SIFT algorithm. SIFT algorithm is scale and rotation invariant, which is powerful for small viewpoint changes in face recognition, but it fails when large viewpoint change exists. In our scheme, Affine SIFT is used for both gallery face and probe face, which generates a series of different viewpoints using affine transformation. Therefore, Affine SIFT allows viewpoint difference between gallery face and probe face. Experiment results show our framework achieves better recognition accuracy than SIFT algorithm on FERET database.