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Park,Mignon 연세대학교 산업기술연구소 1988 논문집 Vol.20 No.2
In this paper, we describe a design of the sensor system using optical fiber. In recognition of an object, the image processing method using CCTV-Camera has been widely used. But a new method with real time and low cost is required only to recognize and classify elements simply in the industrial field. At this point of view, this paper shows a design of the sensor system. The light emitted from the light source is transmitted to an element through optical fiber and the intensity of the reflected light is detected at photo-sensor. It is analysed and processed by means of computer. Then we try to measure the distribution of 3-dimensional displacement of an element or a measurement part. By obtaining the linear normalized operator and weight of each measurement point, we can show that it is possible to recognize an object reliably and quantitatively.
Multiple Face Segmentation and Tracking Based on Robust Hausdorff Distance Matching
Park, Chang-Woo,Kim, Young-Ouk,Sung, Ha-Gyeong,Park, Mignon Korean Institute of Intelligent Systems 2003 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.3 No.1
This paper describes a system for tracking multiple faces in an input video sequence using facial convex hull based facial segmentation and robust hausdorff distance. The algorithm adapts skin color reference map in YCbCr color space and hair color reference map in RGB color space for classifying face region. Then, we obtain an initial face model with preprocessing and convex hull. For tracking, this algorithm computes displacement of the point set between frames using a robust hausdorff distance and the best possible displacement is selected. Finally, the initial face model is updated using the displacement. We provide an example to illustrate the proposed tracking algorithm, which efficiently tracks rotating and zooming faces as well as existing multiple faces in video sequences obtained from CCD camera.
Robust Fuzzy Feedback Linearization Control Based on Takagi-Sugeno Fuzzy Models
Park, Chang-Woo,Park, Mignon Institute of Control 2002 Transaction on control, automation and systems eng Vol.4 No.4
In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.
Robust Stability Analysis of Fuzzy Feedback Linearization Control Systems
Park, Chang-Woo,Lee, Chang-Hoon,Park, Mignon Korean Institute of Intelligent Systems 2002 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.2 No.1
In this paper, we have studied a numerical stability analysis method for the robust fuzzy feedback linearization regulator using Takagi-Sugeno fuzzy model. To analyze the robust stability, we assume that uncertainty is included in the model structure with known bounds. For these structured uncertainty, the robust stability of the closed system is analyzed by applying Linear Matrix Inequalities theory following a transformation of the closed loop systems into Lur'e systems.
Intelligent and Robust Face Detection
Park, Min-sick,Park, Chang-woo,Kim, Won-ha,Park, Mignon Korean Institute of Intelligent Systems 2001 한국지능시스템학회논문지 Vol.11 No.7
A face detection in color images is important for many multimedia applications. It is first step for face recognition and can be used for classifying specific shorts. This paper describes a new method to detect faces in color images based on the skin color and hair color. This paper presents a fuzzy-based method for classifying skin color region in a complex background under varying illumination. The Fuzzy rule bases of the fuzzy system are generated using training method like a genetic algorithm(GA). We find the skin color region and hair color region using the fuzzy system and apply the convex-hull to each region and find the face from their intersection relationship. To validity the effectiveness of the proposed method, we make experiment with various cases.
Park, Chang-Woo,Park, Mignon Elsevier 2004 Information sciences Vol.159 No.1
<P><B>Abstract</B></P><P>In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi–Sugeno (T–S) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. By the proposed estimator, the parameters of the T–S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for indirect adaptive fuzzy control. In order to show the applicability of the proposed estimator, indirect adaptive fuzzy control design examples with the proposed estimator are presented.</P>
Time-Delayed and Quantized Fuzzy Systems: Stability Analysis and Controller Design
Park, Chang-Woo,Kang, Hyung-Jin,Kim, Jung-Hwan,Park, Mignon Institute of Control 2000 Transaction on control, automation and systems eng Vol.2 No.4
In this paper, the design methodology of digital fuzzy controller(DFC) for the systems with time-delay is presented and the qualitative effects of the quantizers in digital implementation of a fuzzy controllers are investigated. We propose the fuzzy feed-back controller whose output is delayed with unit sampling period and period and predicted. the analysis and the design problem considering time-delay become very easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy system with time-delay is solved by linear matrix inequality(LMI) theory. Furthermore, we analyze the stability of the quantized fuzzy system. Our results prove that when quantization os taken into account, one only has convergence to some small neighborhood about origin. We develop a fuzzy control system for backing up a computer-simulated truck-trailer with the consideration of time-delay and quantization effect. By using the proposed method, we analyze the quantization effect to the system and design a DFC which guarantees the stability of the control system in the presence of time-delay.
On-line Parameter Estimator Based on Takagi-Sugeno Fuzzy Models
Park, Chang-Woo,Hyun, Chang-Ho,Park, Mignon Korean Institute of Intelligent Systems 2002 한국지능시스템학회논문지 Vol.12 No.5
In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.