• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.442-450
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• 2011

A measurement system using stereo pattern recognition (SPR) method was configured to measure the rotor blade deformations and motions. An SPR-based measurement system was prepared using six stereo cameras. Through a series of experiments to evaluate the system measurement uncertainty, it was verified that the SPR system had less than 0.2mm standard uncertainty. The combined standard uncertainties for the lead-lag, flapping, and pitching motions were estimated as 0.296mm, 0.209mm, and $0.238^{\circ}$, respectively. The SPR system was installed at a general small-scaled rotor test system at Korea Aerospace Research Institute. The blade motions and elastic deformation were successfully measured under the conditions with rotating speeds of 360rpm or 589rpm, and collective pitch angles of $0^{\circ}$, $4^{\circ}$, or $6^{\circ}$. The advantages of the SPR system was analyzed in comparison with the measurement system used in Higher Harmonic Control Aeroacoustic Rotor Test -II.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.197-204
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• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• Korean Journal of Optics and Photonics
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• v.17 no.1
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• pp.47-53
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• 2006

The Integrated Ballistics Identification Systems (IBIS) is widely used for bullet and casing signature identification. The IBIS obtains a pair of ballistic signatures from two bullets (or casings) using optical microscopy, and estimates a correlation score which can represent the degree of signature match. However, this method largely depends on lighting and surface conditions because optical image contrast is primarily a function of test surface's slope, shadowing, multiple reflections, optical properties, and illumination direction. Moreover, it can be affected with surface height variation. To overcome these problems and improve the identification system, we used well known surface topographic techniques, such as confocal microscopy and white-light scanning interferometry. The measuring instruments were calibrated by a NIST step height standard and verified by a NIST sinusoidal profile roughness standard and a commercial roughness standard. We also suggest a new analysis method for the ballistic identification. In this method, the maximum cross-correlation function CCFmax is used to quantify the degree of signature match. If the compared signatures were exactly the same, CCFmax would be $100\%$.

• The Journal of Information Technology
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• v.7 no.4
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• pp.1-8
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• 2004

The depth information of 3D image lost by projecting 3D-object to 2D-screen for earning image. If depth information is restored and is used to recognize 3D-object, we can make the more effective recognition system. We often use shape from stereo algorithm in order to restore this information. In this paper, we suggest 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In this system, we use the moving vector of object to reduce matching time and In second matching step, the unknown input image is compared with the reference images, which is made with octree codes. Octree codes are used in volume-based representation of a three dimensional object. The result of simulation show that the proposed 3-D object recognition system provides satisfactory performance.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.981-996
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• 2007

In this paper, we describe a method that can recognize gestures by obtaining motion features information with principal factor analysis from sequential gesture images. In the algorithm, firstly, a two dimensional silhouette region including human gesture is segmented and then geometric features are extracted from it. Here, global features information which is selected as some meaningful key feature effectively expressing gestures with principal factor analysis is used. Obtained motion history information representing time variation of gestures from extracted feature construct one gesture subspace. Finally, projected model feature value into the gesture space is transformed as specific state symbols by grouping algorithm to be use as input symbols of HMM and input gesture is recognized as one of the model gesture with high probability. Proposed method has achieved higher recognition rate than others using only shape information of human body as in an appearance-based method or extracting features intuitively from complicated gestures, because this algorithm constructs gesture models with feature factors that have high contribution rate using principal factor analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.136-150
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• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.181-185
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• 1998

Recently, research and developmental direction of communication system is concurrent adopting voice data and face image in speaking to provide more higher recognition rate then in the case of only voice data. Therefore, we present a method of lipreading in speech image sequence by using the 3-D facial shape model. The method use a feature information of the face image such as the opening-level of lip, the movement of jaw, and the projection height of lip. At first, we adjust the 3-D face model to speeching face image sequence. Then, to get a feature information we compute variance quantity from adjusted 3-D shape model of image sequence and use the variance quality of the adjusted 3-D model as recognition parameters. We use the intensity inclination values which obtaining from the variance in 3-D feature points as the separation of recognition units from the sequential image. After then, we use discrete HMM algorithm at recognition process, depending on multiple observation sequence which considers the variance of 3-D feature point fully. As a result of recognition experiment with the 8 Korean vowels and 2 Korean consonants, we have about 80% of recognition rate for the plosives and vowels.

• Smart Media Journal
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• v.11 no.1
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• pp.46-57
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• 2022

In this paper, multi-region based Radial Graph Convolutional Network (MRGCN) algorithm which can perform end-to-end action recognition using the optical flow and gradient of input image is described. Because this method does not use information of skeleton that is difficult to acquire and complicated to estimate, it can be used in general CCTV environment in which only video camera is used. The novelty of MRGCN is that it expresses the optical flow and gradient of the input image as directional histograms and then converts it into six feature vectors to reduce the amount of computational load and uses a newly developed radial type network model to hierarchically propagate the deformation and shape change of the human body in spatio-temporal space. Another important feature is that the data input areas are arranged being overlapped each other, so that information is not spatially disconnected among input nodes. As a result of performing MRGCN's action recognition performance evaluation experiment for 30 actions, it was possible to obtain Top-1 accuracy of 84.78%, which is superior to the existing GCN-based action recognition method using skeleton data as an input.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.109-110
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• 2014

주사전자현미경(Scanning Electron Microscopy: SEM)은 고체상태에서 미세조직과 형상을 관찰하는 데에 가장 다양하게 쓰이는 분석기기로서 최근에 판매되고 있는 고분해능 SEM은 수 나노미터의 분해능을 가지고 있다. 그리고 SEM의 초점심도가 크기 때문에 3차원적인 영상의 관찰이 용이해서 곡면 혹은 울퉁불퉁한 표면의 영상을 육안으로 관찰하는 것처럼 보여준다. 활용도도 매우 다양해서 금속파면, 광물과 화석, 반도체 소자와 회로망의 품질검사, 고분자 및 유기물, 생체시료 nnnnnnnnn와 유가공 제품 등 모든 산업영역에 걸쳐 있다(Fig. 1). 입사된 전자빔이 시료의 원자와 탄성, 비탄성 충돌을 할 때 2차 전자(secondary electron)외에 후방산란전자(back scattered electron), X선, 음극형광 등이 발생하게 되는 이것을 통하여 topography (시료의 표면 형상), morphology(시료의 구성입자의 형상), composition(시료의 구성원소), crystallography (시료의 원자배열상태)등의 정보를 얻을 수 있다. SEM은 2차 전자를 이용하여 시료의 표면형상을 측정하고 그 외에는 SEM을 플랫폼으로 하여 EDS (Energy Dispersive X-ray Spectroscopy), WDS (Wave Dispersive X-ray Spectroscope), EPMA (Electron Probe X-ray Micro Analyzer), FIB (Focus Ion Beam), EBIC (Electron Beam Induced Current), EBSD (Electron Backscatter Diffraction), PBMS (Particle Beam Mass Spectrometer) 등의 많은 분석장치들이 SEM에 부가적으로 장착되어 다양한 시료의 측정이 이루어진다. 이 중 결정구조, 조성분석을 쉽고 효과적으로 할 수 있게 하는 X선 분석장치인 EDS를 SEM에 일체화시킨 장비와 EDS 및 PBMS를 SEM에 장착하여 반도체 공정 중 발생하는 나노입자의 형상, 성분, 크기분포를 측정하는 PCDS(Particle Characteristic Diagnosis System)에 대해 소개하고자 한다. - EDS와 통합된 SEM 시스템 기본적으로 SEM과 EDS는 상호보완적인 기능을 통하여 매우 밀접하게 사용되고 있으나 제조사와 기술적 근간의 차이로 인해 전혀 다른 방식으로 운영되고 있다. 일반적으로 SEM과 EDS는 별개의 시스템으로 스캔회로와 이미지 프로세싱 회로가 개별적으로 구현되어 있지만 로렌츠힘에 의해 발생하는 전자빔의 왜곡을 보정을 위해 EDS 시스템은 SEM 시스템과 연동되어 운영될 수 밖에 없다. 따라서, 각각의 시스템에서는 필요하지만 전체 시스템에서 보면 중복된 기능을 가지는 전자회로들이 존재하게 되고 이로 인해 SEM과 EDS에서 보는 시료의 이미지의 차이로 인한 측정오차가 발생한다(Fig. 2). EDS와 통합된 SEM 시스템은 중복된 기능인 스캔을 담당하는 scanning generation circuit과 이미지 프로세싱을 담당하는 FPGA circuit 및 응용프로그램을 SEM의 회로와 프로그램을 사용하게 함으로 SEM과 EDS가 보는 시료의 이미지가 정확히 일치함으로 이미지 캘리브레이션이 필요없고 측정오차가 제거된 EDS 측정이 가능하다. - PCDS 공정 중 발생하는 입자는 반도체 생산 수율에 가장 큰 영향을 끼치는 원인으로 파악되고 있으며, 생산수율을 저하시키는 원인 중 70% 가량이 이와 관련된 것으로 알려져 있다. 현재 반도체 공정 중이나 반도체 공정 장비에서 발생하는 입자는 제어가 되고 있지 않은 실정이며 대부분의 반도체 공정은 저압환경에서 이루어지기에 이 때 발생하는 입자를 제어하기 위해서는 저압환경에서 측정할 수 있는 측정시스템이 필요하다. 최근 국내에서는 CVD (Chemical Vapor Deposition) 시스템 내 파이프내벽에서의 오염입자 침착은 심각한 문제점으로 인식되고 있다(Fig. 3). PCDS (Particle Characteristic Diagnosis System)는 오염입자의 형상을 측정할 수 있는 SEM, 오염입자의 성분을 측정할 수 있는 EDS, 저압환경에서 기체에 포함된 입자를 빔 형태로 집속, 가속, 포화상태에 이르게 대전시켜 오염입자의 크기분포를 측정할 수 있는 PBMS가 일체화 되어 반도체 공정 중 발생하는 나노입자 대해 실시간으로 대처와 조치가 가능하게 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.