• 융합신호처리학회논문지
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• 제11권2호
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• pp.143-150
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• 2010

무마커 증강현실 시스템은 실내나 옥외 환경에서 자연 물체를 인식하고 매칭하는 기능이 필수적이다. 본 논문에서는 비주얼 서술자와 코드북을 사용하여 특징을 추출하고 자연 물체를 인식하는 기법을 제안한다. 증강현실 응용은 동작 속도와 실시간 성능에 민감하기 때문에, 본 연구에서는 멀티 클래스의 자연 물체 인식에 초점을 두었으며 분류와 특징 추출 시간을 줄이는 것을 포함한다. 훈련과 테스트 과정에서 자연 물체로부터 특징을 추출하기 위해 SIFT와 SURF을 각각 사용하고 그들의 성능을 비교한다. 또한, 클러스터링 알고리즘을 이용하여 다차원의 특징 벡터들로부터 비주얼 코드북을 생성하고 나이브 베이즈 분류기를 이용해 물체를 인식한다.

• 전자공학회논문지B
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• 제31B권5호
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• pp.1-11
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• 1994

In computer graphics since objects atre constructed by lines and curves, the high-speed curve generator is indispensible for computer aided design and simulatation. Since the functions of graphic generation can be represented as a series of matrix operations, in this paper, two kind of the high-speed Bezier curve generator that uses matrix equation and a recursive relation for Bezier polynomials are designed. And B-spline curve generator is designed using interdependence of B-spline blending functions. As the result of the comparison of designed curve generator and reference [5], [6] in the operation time and number of operators, the curve generator with 1-dimensional systolic array processor for matrix vector operation that uses matrix equation for Bezier curve is more effective.

• Journal of information and communication convergence engineering
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• 제16권2호
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• pp.99-105
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• 2018

k-Nearest neighbor join (k-NN Join) is a computationally intensive algorithm that is designed to find k-nearest neighbors from a dataset S for every object in another dataset R. Most related studies on k-NN Join are based on single-computer operations. As the data dimensions and data volume increase, running the k-NN Join algorithm on a single computer cannot generate results quickly. To solve this scalability problem, we introduce the locality-sensitive hashing (LSH) k-NN Join algorithm implemented in Spark, an approach for high-dimensional big data. LSH is used to map similar data onto the same bucket, which can reduce the data search scope. In order to achieve parallel implementation of the algorithm on multiple computers, the Spark framework is used to accelerate the computation of distances between objects in a cluster. Results show that our proposed approach is fast and accurate for high-dimensional and big data.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권4호
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• pp.427-431
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• 2010

다차원 척도법(multidimensional scaling)은 고차원의 데이터를 낮은 차원의 공간에 매핑(mapping)하여 데이터 간의 유사성을 표현하는 방법이다. 이는 주로 자질 선정 및 데이터를 시각화하는 데 이용된다. 그러한 다차원 척도법 중, 전통 다차원 척도법(classical multidimensional scaling)은 긴 수행 시간과 큰 공간을 필요로 하기 때문에 객체의 수가 많은 경우에 대해 적용하기 어렵다. 이는 유클리드 거리(Euclidean distance)에 기반한 $n{\times}n$ 상이도 행렬(dissimilarity matrix)에 대해 고유쌍 문제(eigenpair problem)를 풀어야 하기 때문이다(단, n은 객체의 개수). 따라서, n이 커질수록 수행 시간이 길어지며, 메모리 사용량 증가로 인해 적용할 수 있는 데이터 크기에 한계가 있다. 본 논문에서는 이러한 문제를 완화하기 위해 GPGPU 기술 중 하나인 CUDA와 분할-정복(divide-and-conquer)기법을 활용한 효율적인 다차원 척도법을 제안하며, 다양한 실험을 통해 제안하는 기법이 객체의 개수가 많은 경우에 매우 효율적일 수 있음을 보인다.

• 한국정밀공학회지
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• 제32권6호
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• pp.543-551
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• 2015

In this study, a novel method for dimension measurement of large-scale moving objects using stereo camera with 2-degree of freedom (2-DOF) mechanism is presented. The proposed method utilizes both the advantages of stereo vision technique and the enlarged visibility range of camera due to 2-DOF rotary mechanism in measuring large-scale moving objects. The measurement system employs a stereo camera combined with a 2-DOF rotary mechanism that allows capturing separate corners of the measured object. The measuring algorithm consists of two main stages. First, three-dimensional (3-D) positions of the corners of the measured object are determined based on stereo vision algorithms. Then, using the rotary angles of the 2-DOF mechanism the dimensions of the measured object are calculated via coordinate transformation. The proposed system can measure the dimensions of moving objects with relatively slow and steady speed. We showed that the proposed system guarantees high measuring accuracy with some experiments.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.435-446
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• 2020

With the ability to learn rules from training data, the machine learning model can classify unknown objects. At the same time, the dimension of hyperspectral data is usually large, which may cause an over-fitting problem. In this research, an identification methodology of tea diseases was proposed based on spectral reflectance and machine learning, including the feature selector based on the decision tree and the tea disease recognizer based on random forest. The proposed identification methodology was evaluated through experiments. The experimental results showed that the recall rate and the F1 score were significantly improved by the proposed methodology in the identification accuracy of tea disease, with average values of 15%, 7%, and 11%, respectively. Therefore, the proposed identification methodology could make relatively better feature selection and learn from high dimensional data so as to achieve the non-destructive and efficient identification of different tea diseases. This research provides a new idea for the feature selection of high dimensional data and the non-destructive identification of crop diseases.

• 한국정밀공학회지
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• 제22권9호
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• pp.115-122
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• 2005

Errors resulting from magnification variations of a optical system are largely generated in three-dimensional shape measurements based on depth-from-focus. In the case of measuring the surface morphology of tiny objects based on DFF, images are acquired with a very small interval so that magnification changes can be minimized. However, the magnification variations are actually existed in the acquired images and so focus measures are wrongly or ambiguously extracted. In this paper, a methodology with linear magnification calibrations, based on DFF, is proposed to make more accurate measurement in surface morphology with high depth discontinuity, compared with previous ones. Several experiments show that the proposed method outperforms existing ones without magnification calibrations.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.1742-1747
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• 2003

When a shock wave is discharged from the exit of a duct, complicated flow is formed near the duct exit. The flow field is much more complicated under the ground effects or any other objects near the exit of a duct, such as the circumstance near the exit of the high-speed railway tunnel. The resulting flow is essentially three-dimensional unsteady with the effects of strong compressibility. In the current study, three-dimensional flow fields of the weak shock wave which is discharged from the exit of a duct are numerically investigated using a CFD method. Computations are performed for the weak shock wave in the range below 1.5. The results obtained show that the directivity and magnitude of the weak shock discharged strongly depend upon the Mach number of initial shock wave and are significantly influenced by the ground effects.

• 한국정밀공학회지
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• 제23권7호
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• pp.168-176
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• 2006

Nowadays, Three dimensional printing (3DP) technique that is one of solid freeform fabrication (SFF) technology has been notable issue, and has been applied by various fields. The SFF system can fabricate three dimensional objects of solid freeform with high speed and low cost using ink jet printing technology. In this research, a SFF system to analyze 3DP process technology is developed. We applied sliding mode control with sliding perturbation observer (SMCSPO) algorithm and minimized position error to the developed SFF system. We analyzed and optimized process variables such as jetted volume, layer thickness, powder bed and so on experimentally. Also. the dimensional error of a developed SFF system is evaluated. Finally, the feasibility of application to bio manufacturing is presented through successful fabrication of teeth and cranium model.

• 조명전기설비학회논문지
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• 제29권11호
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• pp.18-27
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• 2015

In this paper, we proposed the spinning right-angle stereo vision system to center the shifted object on 3-dimensional image using a human eyesight-like, and the system is reconstructed with conventional stereo vision system. In this proposed system, the centering results of objects on the 3-dimensional image are very good, and we got the parameter ratios 89~112% for the real measurement values. Therefore, the suggested the spinning right-angle stereo vision system have a high possibilities to be applied to many industrial system parts and to be used for robot system, automatic system, and etc.