• The Journal of Society for e-Business Studies
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• v.1 no.1
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• pp.69-92
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• 1996

An Integrated Data Environment (IDE) is the end state of the CALS vision. It refers to an environment where all the data generated from the entire lifecycle activities of a product can be shared by anyone that participates in the management. engineering, manufacturing, or support of the product, although the data are geographically distributed and are maintained in heterogeneous platforms. The primary purpose of this paper is to introduce the fundamental concept, architecture, and core implementation technology of an IDE. The secondary purpose is to suggest some strategic directions to the planning staffs in both government and industry. and to suggest some research issues to the researchers in academia. The reference architecture of an IDE being developed by the US DoD and that of NIIIP (National Industrial Information Infrastructure Protocol) being developed by a consortium are discussed. Two principal issues of implementing an integrated database, i.e., distributed object computing including CORBA and multi-database system (MDBS) are reviewed. As a conclusion. the author suggests that daring investment in prototyping an IDE by a nationwide consortium is essential to keep up with the advanced countries in CALS implementation.

• Journal of the Korean Professional Engineers Association
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• v.34 no.1
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• pp.49-52
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• 2001

It is expected that transportation sector will develope to a systematic and multi-disciplinary way in which transportation, information and electronic technologies are harmonized. This will be the way that the 21st century demand. To be prepared for such development, sharing of information from different sources through a integrated approach is essential. Also an active role of specialized staff are required to achieve a integrated control and management. The specialized staff should do his best for his task with appropriate specialty, a sense of responsibility, a progressive mind and a vision. He also make much effort to enhance and keep up-to-date his specialty. Then we can modestly look forward to a specialized Information society in the 21s1 century.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1347-1355
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• 2019

Deep learning approach based on convolution neural network (CNN) has extensively studied in the field of computer vision. However, periocular feature extraction using CNN was not well studied because it is practically impossible to collect large volume of biometric data. This study uses the ResNet model which was trained with the ImageNet dataset. To overcome the problem of insufficient training data, we focused on the training of multi-layer perception (MLP) having simple structure rather than training the CNN having complex structure. It first extracts features using the pretrained ResNet model and reduces the feature dimension by principle component analysis (PCA), then trains a MLP classifier. Experimental results with the public periocular dataset UBIPr show that the proposed method is effective in person authentication using periocular region. Especially it has the advantage which can be directly applied for other biometric traits.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.8
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• pp.172-179
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• 2002

In this paper, an efficient reverse engineering method for free-formed surfaces is proposed based on the integration of a repetitive digitizing method and vision system. In recent reverse engineering process, the equi-interval digitization method is being used since the surface information is not known. If more accurate results are required, the number of measuring point should be increased appropriately. Thus, such measuring process tends to result in too dense data including useless information, and cause excessive measuring time. This problem can be improved by applying repetitive digitizing method and image process technique, which is proposed in this paper. The proposed methods are validated through appropriate simulation and experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.870-876
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• 2017

In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.21-28
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.31-36
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• 2005

Intelligent Space (iSpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment comes to have intelligence. In iSpace, the locations of multiple humans and other objects are obtained and tracked by using multiple camera and color-based method. In addition, we describe a context-aware information system which is based on Spatial-Knowledge-Tags (SKT). SKT system enables humans to access information and data by using spatial location of human and stored information in storage. The proposed tracking method is applied to the intelligent environment and its performance is verified by the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.449-452
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• 2005

For home networking system with a function of air quality monitoring, a wireless sensor module with several air quality monitoring sensors was developed for indoor environment monitoring system in home networking. The module has various enlargements for various kinds of sensors such as humidity sensor, temperature sensor, CO2 sensor, flying dust sensor, and etc. The developed wireless module is very convenient to be installed on the wall of a room or office, and the sensors in the module can be easily replaced due to well designed module structure and RF connection method. To reduce the system cost, only one RF transmission block was used for sensors' signal transmission to 8051 microcontroller board in time sharing method. In this home networking system, various indoor environmental parameters could be monitored in real time from RF wireless sensor module. Indoor vision was transferred to client PC or PDA from surveillance camera installed indoor or desired site. Web server using Oracle DB was used for saving the visions by web-camera and various data from wireless sensor module.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.372-378
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• 2009

For effective mobility control of unmanned ground vehicles in outdoor off-road environments, terrain cover classification technology using passive sensors is vital. This paper presents a novel method far terrain classification based on color and texture information of off-road images. It uses a neural network classifier and wavelet features. We exploit the wavelet mean and energy features extracted from multi-channel wavelet transformed images and also utilize the terrain class spatial coordinates of images to include additional features. By comparing the classification performance according to applied features, the experimental results show that the proposed algorithm has a promising result and potential possibilities for autonomous navigation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.3-100
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• 2002

This paper presents the method for detection and tracking of multiple humans robustly in mobile platform. The perception of human is performed in real time through the processing of images acquired from a moving stereo vision system. We performed multi-cue integration such as human shape, skin color and depth information to detect and track each human in moving background scene. Human shape is measured by edge-based template matching on distance transformed image. Improving robustness for human detection, we apply the human face skin color in HSV color space. And we could increase the accuracy and the robustness in both detection and tracking by applying random sampling stochastic estimati...