• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.306-311
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• 1996

This paper discusses the maintenance of the water level of steam generators at its programmed value. The process, the water level of a steam generator, has the nonminimum phase property. So, it causes a reverse dynamics called a swell and shrink phenomenon. This phenomenon is severe in a low power condition below 15 %, in turn makes the start-up of the power plant too difficult. The control algorithm used here incorporates a pole-assignment scheme into the minimum variance strategy and we use a parallel adaptation algorithm for the parameter estimation, which is robust to noises. As a result, the total control system can keep the water level constant during full power by locating closed-loop poles appropriately, although the process has the characteristics of high complexity and nonlinearity. Also, the extra perturbation signals are added to the input signal such that the control system guarantee persistently exciting. In order to confirm the control performance of a proposed pole-assignment self-tuning controller we perform a computer simulation in full power range.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.1
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• pp.1-16
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• 2009

In this paper, we introduce two-phase versions of RoeM and AUSMPW+ schemes. Both schemes are originally developed for the gas dynamic problems, and have shown superior accuracy, efficiency and robustness. A new shock discontinuity sensing term is derived from the mixture equation of state, which is commonly used in the RoeM and AUSMPW+ schemes for the stable numerical flux calculation. The developed two-phase versions of the schemes are applied to several liquid-gas, large property discrepancy two-phase test problems, including several shock stability test problems. The results show that both schemes maintain the merits exhibited in gas dynamic problems even in two-phase flows.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.348-351
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• 2004

In this paper, we propose the face recognition method using Harr wavelet transform and 2D PCA. While previous PCA computed the covariance matrix by using one dimensional vectors, 2D PCA computed the covarinace matrix by using direct two dimensional image and extracted feature vector by solving eigenvalue problem. To gain the face image having the low dimension and robust property, the proposed method uses wavelet transformation. We apply the LL band image data to 2D PCA for face recognition. The experimental results indicate that our method improves recognition rate than 2D PCA into original image.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1281-1287
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• 2013

In order to prevent illegal video copies, many video fingerprints have been developed. Video fingerprints should be robust from various video transformations and have high discriminative powers. In general, video fingerprints are generated from three feature spaces such as luminance, gradient, and DCT coefficients. However, there is a few study for the robustness and discrimination according to feature spaces. Thus, we analyzed the property of each feature space by video copy detion task with the robustness and the discrimination of video fingerprints. We generated three video fingerprints from these feature spaces using a same algorithm. In our test, a video fingerprint. based on DCT coefficient outperformed others because the discrimination of it was higher.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.113-115
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• 2005

This thesis presents a method for 3D modeling of facial expression from frontal and mirror-reflected multi-image. Since the proposed system uses only one camera, two mirrors, and simple mirror's property, it is robust, accurate and inexpensive. In addition, we can avoid the problem of synchronization between data among different cameras. Mirrors located near one's cheeks can reflect the side views of markers on one's face. To optimize our system, we must select feature points of face intimately associated with human's emotions. Therefore we refer to the FDP (Facial Definition Parameters) and FAP (Facial Animation Parameters) defined by MPEG-4 SNHC (Synlhetic/Natural Hybrid Coding). We put colorful dot markers on selected feature points of face to detect movement of facial deformation when subject makes variety expressions. Before computing the 3D coordinates of extracted facial feature points, we properly grouped these points according to relative part. This makes our matching process automatically. We experiment on about twenty koreans the subject of our experiment in their late twenties and early thirties. Finally, we verify the performance of the proposed method tv simulating an animation of 3D facial expression.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.973-978
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• 2005

In this paper, we investigate an improved mobile robot localization method using Kalman filter. The highlight of the paper lies in the formulation of combined Kalman filter and its application to mobile robot experiment. The combined Kalman filter is a kind of extended Kalman filter which has an extra degree of freedom in Kalman filtering recursion. It consists of the standard Kalman filter, i.e., the predictor-corrector and the perturbation estimator which reconstructs unknown dynamics in the state transition equation of mobile robot. The combined Kalman filter (CKF) enables to achieve robust localization performance of mobile robot in spite of heavy perturbation such as wheel slip and doorsill crossover which results in large odometric errors. Intrinsically, it has the property of integrating the innovation in Kalman filtering, i.e., the difference between measurement and predicted measurement and thus it is so much advantageous in compensating uncertainties which has not been reflected in the state transition model of mobile robot. After formulation of the CKF recursion equation, we show how the design parameters can be determined and how much beneficial it is through simulation and experiment for a two-wheeled mobile robot under indoor GPS measurement system composed of four ultrasonic satellites. In addition, we discuss what should be considered and what prerequisites are needed to successfully apply the proposed CKF in mobile robot localization.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.20-24
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• 2006

In this paper, we focused on the real time implementation of a speech recognition system with medium size of vocabulary considering its application to a mobile phone. First, we developed the PC based variable vocabulary word recognizer having the size of program memory and total acoustic models as small as possible. To reduce the memory size of acoustic models, linear discriminant analysis and phonetic tied mixture were applied in the feature selection process and training HMMs, respectively. In addition, state based Gaussian selection method with the real time cepstral normalization was used for reduction of computational load and robust recognition. Then, we verified the real-time operation of the implemented recognition system on the TMS320C6201 EVM board. The implemented recognition system uses memory size of about 610 kbytes including both program memory and data memory. The recognition rate was 95.86% for ETRI 445DB, and 96.4%, 97.92%, 87.04% for three kinds of name databases collected through the mobile phones.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.1-7
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• 2004

The rapid growth of digital media and communication networks has created an urgent need for self-contained data identification methods to create adequate intellectual property right(IPR) protection technology. In this paper we propose a new watermarking method that could embed the gray-scale watermark logo in low frequency coefficients of discrete wavelet transform(DWT) domain as the marking space by using our Linear Bit-eXpansion(LBX) interleaving of gray-scale watermark, to use lots of watermark information without distortion of watermarked image quality and particularly to be robust against attack which could remove a part of image. Experimental results demonstrated the high robustness in particular against attacks such as image cropping and rotation which could remove a part of image.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.521-524
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• 2004

Recently, acgis of authentication and crcator's copyright has become a matter of great concern by the diffusion of multimedia technique and the growth of the internet and the easily duplicated property of digital data. Consequently, many active researches have been made to protect copyright and to assure integrity by inserting watermark into the digital data. In this paper, watermark is repealed through the entire image and adapted to the content of the image. Achieved by an underlying process of transforming the digital image to the frequency domain by wavelet transform, which has three (vertical, horizontal, diagonal) directions and Multi-resolution features, and then choosing frequency area inferior to the human perceptibility and significant for invisible and robust watermark. We realize wavelet based image watermarking using Machine Vision of LabVIEW.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.209-215
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• 2018

Recent research in animal behavior has shown that gradient information plays an important role in finding food and home. It is also important in optimization of performance because it indicates how the inputs should be adjusted for maximization/minimization of a performance index. We introduce perturbation as an additional input to obtain gradient information. Unlike the typical approach of calculating the gradient from the derivative, the proposed processing is very robust to noise since it is performed as a summation. Experimental results prove the validity of the process of spatial gradient acquisition. Quantitative indices for measuring the effect of the amplitude and the frequency are developed based on linear regression analysis. Drones are very useful for environmental monitoring and an autonomous path planning is required for unstructured environment. Guiding the drone for finding the origin of the interested physical property is done by estimating the gradient of the sensed value and generating the drone trajectories in the direction which maximizes the sensed value. Simulation results show that the proposed method can be successfully applied to identify the source of the physical quantity of interest by utilizing it for path planning of an autonomous drone in 3D environment.