• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.129-136
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• 2005

The damped least-squares inversion has become a most popular method in finding the solution in geophysical problems. Generally, the least-squares inversion is to minimize the object function which consists of data misfits and model constraints. Although both the data misfit and the model constraint take an important part in the least-squares inversion, most of the studies are concentrated on what kind of model constraint is imposed and how to select an optimum regularization parameter. Despite that each datum is recommended to be weighted according to its uncertainty or error in the data acquisition, the uncertainty is usually not available. Thus, the data weighting matrix is inevitably regarded as the identity matrix in the inversion. We present a new inversion scheme, in which the data weighting matrix is automatically obtained from the analysis of the data resolution matrix and its spread function. This approach, named 'extended active constraint balancing (EACB)', assigns a great weighting on the datum having a high resolution and vice versa. We demonstrate that by applying EACB to a two-dimensional resistivity tomography problem, the EACB approach helps to enhance both the resolution and the stability of the inversion process.

• Korean Journal of Optics and Photonics
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• v.15 no.6
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• pp.583-590
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• 2004

The autofocus is one of the important processes in the automated vision inspection or measurements using optical microscopes, because it influences the measuring accuracy. In this paper, we used the confocal microscope configuration based on not a pinhole but a single-mode optical fiber. A single mode fiber has the functions of source and detector by applying the reciprocal scheme. As a result, we acquired a simple system configuration and easy alignment of the optical axis. Also, we embodied a fast autofocus system by acquiring the focus error signal through a source modulation technique. The source modulation technique can effectively reduce physical disturbances compared with objective lens modulation, and it is easily applicable to general optical microscopes. The focus error signal was measured with respect to the modulation amplitude, reflectance of the specimen and inclination angle of the measuring surface. The performance of the proposed autofocus system was verified through autofocusing flat mirror surface. In addition, we confirmed that source modulation rarely degrades the depth resolution by the comparison between the FWHMs of axial response curves.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.2
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• pp.23-30
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• 2007

This study attempts to propose an appropriate method of using digital medical imaging equipments, by studying the effects of automatic exposure control(AEC), grid ratio and the change of radiography distance on the patient dose and detertor acquisition dose during the procedure of acquiring image through a digital medical imaging detector. The change of dose following the change of grid ratio's exposure and radiography distance was measured, by using an abdominal phantom organized with tissue equivalent materials in an amorphous silicon thin film transistor detecter installed with AWC. The case to use grid ratio 12 : 1, focal distance 180cm to radiography distance 110cm in AEC, the patient dose increased rather when we used grid ration 10 : 1, focal distance 110cm. When AEC was not used,the dose necessary for image acquisition decreased as the grid ratio became higher and the distance became further. but detector acquisition dose was not reduced when in applied AEC. When purchasing digiral medical imaging equipments, optional items such as AEC and grid shall be accurately selected to satisfy the use of the equipments. Radiography error made by radiation technologist and unnenessary patient dose can be reduced by selecting equipments with a radiography distance marker equipment when it did not apply AEC. These equipments can also be helpful in maintaining high imaging quality, one of the merits of digital detectors.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.34-43
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• 2008

This paper presents a system for recognizing sunglasses and a mask of an ATM (Automatic Teller Machine) user. The proposed system extracts firstly facial contour, then from this extraction results it estimates the regions of eyes and mouth. Finally, it recognizes sunglasses and a mouth using Histogram Indexing based on those regions. We adopt a face shape model to be able to extract facial contour and to estimate the regions of eyes and mouth when those regions are occluded by sunglasses and a mask. To improve the fitting accuracy of the shame model, we adopt 2-step face detection method and conduct fitting several times by varying the initial position of the model instance. To achieve a good performance of the face detection method based on a background model, we enable the system to automatically update the background model. In experiment, we present some experiments on setting parameters of the system with images taken from in our laboratory, and demonstrate the results of recognizing sunglasses and a mask.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.702-709
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• 2010

The performance of mass segmentation is greatly influenced by an initial position of a mass. Some researchers performed mass segmentation with the initial position of a mass given by radiologists. The purpose of our research is to find the initial position for mass segmentation and to notify the segmented mass to radiologists without any additional information on mammograms. The proposed system consists of breast segmentation by region growing and opening operations, decision of an initial seed with characteristics of masses, and mass segmentation by a level set segmentation. A seed for mass segmentation is set based on mass scoring measure calculated by block-based variances and masked information in a sub-sampled mammogram. We used a DDSM database to evaluate the system. The accuracy of mass detection is 78% sensitivity at 4 FP/image, and it reached 92% if multiple views for masses were considered.

• Journal of Advanced Navigation Technology
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• v.11 no.2
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• pp.154-162
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• 2007

This paper verifies the performance of the wireless-signal map-matching (WSMM) method that is recently proposed to mitigate the effects of non-line-of-sight (NLOS) error in positioning under wireless terrestrial network environments. The WSMM method is the new positioning technology that estimates and compensate the NLOS errors by processing the bulks of anonymous measurements at unknown locations that are collected randomly and automatically. The WSMM method would be advantageous for various configurations of future ubiquitous sensor networks since it is based on the existing network configuration for communication and it requires no additional hardware in base stations and mobile handsets. It is shown that the application of the WSMM concept to the real CDMA pilot strength measurment message (PSMM) actually mitigates the NLOS error effects and improves overall positioning accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1524-1530
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• 2016

Recently, research about an electronic attendance-absence recording system has been actively carried out using smart devices. Using an electronic attendance-absence recording system, professors can check their students' attendance on a real-time basis and manage their attendance records. In this paper, we proposed a real-time electronic attendance-absence recording system using face detection and face recognition based on web application. It can solve the spatial, temporal, cost issues belong to electronic attendance-absence recording system using AIDC(Automatic Identification and Data Capture). A proposed system is running on web server and made by HTML5(Hyper Text Markup Language ver.5). So professor connect to server using mobile web browser on mobile device and real-time manage electronic attendance-absence recording with real-time send or receive image data. In addition, the proposed system has an advantage capable of installation and operation, regardless of the operating system because it operates based on the Python flask framework.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.431-435
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• 2008

2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판과 구 차량 번호판이 혼합되어 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 형태학적 특징 및 차 연산과 ART2 알고리즘을 이용한 차량 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 차량 번호판 영상에서 차 연산을 이용하여 에지를 추출한 후에 블록 이진화를 한다. 이진화 된 차량 영상에서 신 구 차량 번호판의 형태학적 특성을 8방향 윤곽선 추적 알고리즘에 적용하여 잡음 영역을 제거하고, 차량의 번호판 영역을 추출한다 추출된 번호판 영역에 대하여 평균 이진화와 최대 최소 이진화를 적용하여 번호판의 개별 영역에 대한 형태학적 특성을 고려하여 잡음을 제거하고, Labeling 알고리즘을 적용하여 개별 문자를 추출한 후에 결합한다. 이렇게 분류된 개별 문자 및 숫자 코드를 ART2 알고리즘에 적용하여 학습 및 인식을 한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 녹색 번호판과 흰색 번호판 이미지 각각 100장을 대상으로 실험한 결과, 제시 된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.927-933
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• 2020

This paper presents a fuel quantity measurement system (FQMS) for an aircraft supplementary fuel tank considering the change of aircraft attitude. The developed FQMS consists of fuel sensors, a signal process unit, an indicator and a software to estimate the fuel quantity from the sensor data. To replicate the change of the roll and pitch attitude on the ground, the test simulator is developed in this work. Using the test simulator, the sensor data at various fuel quantities, roll and pitch angles are automatically measured to build a training data set. The data-driven software to estimate the fuel quantity is then developed using a trilinear interpolation method with the training data set. The developed FQMS is verified by investigating the fuel estimation error of the test data set that we know the true values. Through the test, it is confirmed that the error of the developed FQMS system satisfies the criteria of TSO-C55 document.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.413-417
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• 2007

2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판 차량이 꾸준히 증가하고 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차 관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 신 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 지능형 신 자동차 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 신 차량 영상을 그레이 레벨로 변환한 후에 블록 이진화한다. 블록 이진화된 차량 영상을 대상으로 차량의 형태학적 특징을 적용하여 잡음을 제거한 후, 번호판 영역을 추출한다. 추출된 번호판 영역에 대해 Grassfire 알고리즘을 적용하여 개별 코드를 추출한다. 차량 번호판을 인식하기 위하여 추출된 개별 코드를 퍼지 ART 알고리즘을 적용하여 학습 및 인식한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 100장의 차량 영상을 대상으로 실험한 결과, 제안된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.