• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.16-29
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• 1993

The objective of this research is in the development of a flexible 3-dimensional inspection system for the sculptured surface by integrating the Coordinate Measuring Machine (CMM), CAD database, and vision system. To achieve the proposed flexible inspection system, two research categories are discussed in the study: new inspection planning method includes a new measuring point selection method and various new probe path generation methods. The object recognition and localization process for the unknown surface can be easily carried out by introducing a new concept called "Z-Layer". The experimental results indicate that the developed flexible inspection system, with the proposed algorithm, can be inplemented in real situation.situation.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.70-77
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• 2014

This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1920-1926
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• 2006

With social interest, there hie been a lot of research on the Service Robot but now we are faced with the limitation of single platform. The alternative plan is the Ubiquitous-based Service Robot connected with a Ubiquitous network to overcome this limitation. Systems using RFID(Radio frequency Identification) and supersonic waves appeared for functions such as recognition of surroundings through Ubiquitous Sensor Networks. This was applied to the real robot and we have got good results. However, this has several limitations to applying to low power-based Sensor Network For example, if RFID uses a passive Sensor, the rate of recognition with the distance is limited. In case of supersonic waves, high power is required to drive them. Therefore, we intend to develop RSSI position recognition system on the basis of embodying a Sensor Network Module in this thesis. This RSSI position recognition system only measures RSSI of signals from each sensor nod. then converts them into distances and calculates the position. As a result, we can still use low power-based Sensor Network and overcome the limitation according to distance as planning Ad-Hoc Network.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.376-382
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• 2010

We propose a novel method to precisely detect car license plates by locating main characters, which are printed with large font size. The regions of the main characters are directly detected without detecting the plate region boundaries, so that license regions can be detected more precisely than by other existing methods. To generate a binary image, multiple thresholds are applied, and segmented regions are selected from multiple binarized images by a criterion of size and compactness. We do not employ any character matching methods, so that many candidates for main character groups are detected; thus, we use a neural network to reject non-main character groups from the candidates. The relation of the character regions and the intensity statistics are used as the input to the neural network for classification. The detection performance has been investigated on real images captured under various illumination conditions for 1000 vehicles. 980 plates were correctly detected, and almost all non-detected plates were so stained that their characters could not be isolated for character recognition. In addition, the processing time is fast enough for a commercial automatic license plate recognition system. Therefore, the proposed method can be used for recognition systems with high performance and fast processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6420-6426
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• 2013

The indoor areas for the commercial use of automatic monitoring systems of mobile robot localization improves the cognitive abilities and the needs of the environment with this emerging and existing mobile robot localization, and object recognition methods commonly around its great sensor are leveraged. On the other hand, there is a difficulty with a problem-solving self-location estimation in indoor mobile robots using only the sensors of the robot. Therefore, in this paper, a self-position estimation method for an enhanced and effective mobile robot is proposed using a marker and CCTV video that is already installed in the building. In particular, after recognizing a square mobile robot and the object from the input image, and the vertices were confirmed, the feature points of the marker were found, and marker recognition was then performed. First, a self-position estimation of the mobile robot was performed according to the relationship of the image marker and a coordinate transformation was performed. In particular, the estimation was converted to an absolute coordinate value based on CCTV information, such as robots and obstacles. The study results can be used to make a convenient self-position estimation of the robot in the indoor areas to verify the self-position estimation method of the mobile robot. In addition, experimental operation was performed based on the actual robot system.

• Journal of the HCI Society of Korea
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• v.13 no.4
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• pp.15-23
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• 2018

A lot of games are supposed to play through controller operations, such as mouse and keyboard rather than user's physical movement. These games have limitation that causes the user lack of movement. Therefore, this study will solve the problems that these traditional game systems have through the development of a motion-producing system, and provide users more realistic system. It recognizes the user's position in a given space and provides a mobile augmented reality system that interacts with virtual game characters. It uses augmented reality technology to make users feel as if virtual characters exist in real space and it designs a mobile game system that uses armband controllers that interact with virtual characters.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.2
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• pp.126-132
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• 2012

The technique for estimation of sound source direction is one of the important methods necessary for various engineering fields such as monitoring system, military services and so on. As a new approach for estimation of sound source direction, this paper propose the bio-mimetic localization sensor based on mechanically coupling structure motivated by hearing structure of fly, Ormia Ochracea. This creature is known for its outstanding recognition ability to the sound which has large wavelength compared to its own size. ITTF (Inter-Tympanal Transfer Function) which is the transfer function between displacements of the tympanal membranes on each side has the all inter-tympanal information dependent on sound direction. The peak and notch features of desired ITTF can be generated by using the appropriate mechanical properties. A example of estimation of sound source direction using generated ITTF with monotonically changing notch and peak patterns is shown.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1295-1302
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• 2010

This paper proposed indoor location recognition method based on RSSI(received signal strength indication) using the LVQ network. In order to verify the effectiveness of the proposed method, we performed experiments, and then compared to the conventional triangularity measurement method. In the experiments, we set up the system to the laboratory, divided the 40 section, and installed 6 nodes as a reference node. We obtained the log-normal path loss model of wireless channels, RSSI converted into the distance. The distance values used as the input of LVQ. To learn the LVQ network, we set the target values as section indices. In the experiments, we determined the optimal number of subclass, and confirmed that the success rate of training phase was 96%, test phase was 91%.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.403-409
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• 2007

Contourlet transform is an extention of the wavelet transform in two dimensions using the multiscale and directional fillet banks. The contourlet transform has the advantages of multiscale and time-frequency-localization properties of wavelets, but also provides a high degree of directionality. In this paper, we propose a face recognition system based on fusion methods using contourlet transform and PCA. After decomposing a face image into directional subband images by contourlet, features are obtained in each subband by PCA. Finally, face recognition is performed by fusion technique that effectively combines similarities calculated respectively In each local subband. To show the effectiveness of the proposed method, we performed experiments for ORL and CBNU dataset, and then we obtained better recognition performance in comparison with the results produced by conventional methods.