• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.373-376
• /
• 2009

영상처리 기술은 인간의 시각에 기반을 둔 영상정보와 관련된 분야에서 중요한 기반 기술로써 현재 여러 분야에서 연구가 활발하게 진행 중이다. 여러 응용 분야에서 사용되는 영상처리의 세부 기술범위는 영상 변환, 영상 개선, 영상 복원, 영상 압축등과 같이 다양하며, 이런 영상처리 기술의 중요한 연구 목표 중의 하나는 정확한 정보 추출을 위한 영상정보의 개선에 있다. 영상정보의 개선은 영상의 해석과 인식을 위한 기본적인 과제이며, 영상에서 나타날 수 있는 잡음을 제거하는 영상처리 기술이 영상정보 개선의 한 분야라고 할 수 있다. 영상정보 개선을 위한 기존의 필터링 알고리즘은 잡음제거율이 높은 만큼 경계선의 보존이 어렵다는 단점이 있으며, 이를 보완하기 위해 다른 영상처리 알고리즘을 함께 응용하여 처리함으로써 처리시간이 증가되고 원 영상의 중요한 정보를 훼손할 가능성이 존재한다. 따라서 본 논문에서는 기존의 필터링 알고리즘의 문제점을 개선하는 동시에 잡음 제거율을 높일 수 있는 Fuzzy Mask Filter 알고리즘을 제안한다. Fuzzy Mask Filter 알고리즘은 마스크에서 얻은 정보를 Fuzzy Logic에 적용하여 임계값을 구하며, 구해진 임계값을 기준으로 출력영상의 화소값을 결정하는 알고리즘이다. 본 논문에서 제안한 알고리즘의 효율성을 검증하기 위해 Impulse 잡음과 Salt pepper 잡음을 임의로 생성하여 기존의 알고리즘과 비교한 결과, 제안된 방법이 잡음 영상에 존재하는 픽셀 정보를 훼손하지 않고 잡음을 효과적으로 제거한 것을 확인할 수 있었다.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.6
• /
• pp.61-70
• /
• 2011

In this paper, it is realized an image filter for a noise elimination using a recurrent neural networks with fuzzy. The proposed fuzzy neural networks structure is to converge weights and the number of iteration for a certain value by using basically recurrent neural networks structure and is simplified computation and complexity of mathematics by applying the hybrid fuzzy membership function operator. In this paper, the proposed method, the recurrent neural networks applying fuzzy which is collected a certain value, has been proved improving average 0.38dB than the conventional method, the generalied recurrent neural networks, by using PSNR. Also, a result image of the proposed method was similar to the original image than a result image of the conventional method by comparing to visual images.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.5
• /
• pp.609-614
• /
• 2009

The purpose of this paper is to design the metal object detection system for drive inside protection. To do this, we propose the algorithm for designing the color filter that can detect the metal object using fuzzy theory and the algorithm for detecting area of the driver's face using fuzzy skin color filter. Also, by using the proposed algorithm, we propose the algorithm for detecting the metallic object candidate regions. And, the metallic object color filter is then applied to find the candidate regions. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.366-366
• /
• 2000

In this paper, an adaptive neuro-fuzzy filter using the conditional fuzzy c-means(CFCM) methods is proposed. Usualy, the number of fuzzy rules exponentially increases by applying the grid partitioning of the input space, in conventional adaptive neuro-fuzzy inference system(ANFIS) approaches. In order to solve this problem, CFCM method is adopted to render the clusters which represent the given input and output data. Parameter identification is performed by hybrid learning using back-propagation algorithm and total least square(TLS) method. Finally, we applied the proposed method to the nonlinear channel equalization problem and obtained a better performance than previous works.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.5
• /
• pp.462-466
• /
• 2007

This paper proposes an automatic bandwidth control method for the performance improvement of Binary Amplitude Shift Keying (BASK) system for Giga-Bit Modem in millimeter band. In order to improve the performance of the BASK system with a fixed bandwidth, the proposed method is to adjust a bandwidth of low pass filter in receiver using the fuzzy system. The BASK system consists of a high speed shutter of the transmitter and a counter and a repeater of receiver. The repeater consists of four stage converters, and a converter is constructed with a low pass filter and a limiter. The inputs to the fuzzy system are the reminder and integral of remainder of counter, and output is a bandwidth. We used a Viterbi algorithm to find the optimum detection from the output of the counter. Simulation results showed that the proposed system improves the performance compared to the fixed bandwidth.

• Journal of information and communication convergence engineering
• /
• v.6 no.4
• /
• pp.421-424
• /
• 2008

In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

• Journal of Biomedical Engineering Research
• /
• v.15 no.3
• /
• pp.355-364
• /
• 1994

The most important requirement for the controller of a prosthetic arm is that it has a high fidelity discriminator where the motion control may be performed open loop using EMG signals as a control source. Therefore, it is very effective method to reduce the influence of misclassification of classifier for the total system performance. This paper presents the new function discrimination method which combines MLP classifier and frizzy filter by stages for the requirement. The major advantage of MLP is a consistent learning capability for the easy adaptation to environments. The fuzzy filter uses all informations of MLP outputs and prior EMG activity informations which increase as the experience increases. That property is superior to one which uses maximum output of MLP in view of information amounts and quality. Simulation result shows that proposed method is superior to the probabilistic model, MLP model and the combined model of both in the respect of discrimination quaity.

• Journal of information and communication convergence engineering
• /
• v.15 no.2
• /
• pp.131-136
• /
• 2017

Chest X-ray image cannot be focused in the same manner as optical lenses and the resultant image generally tends to be slightly blurred. Therefore, appropriate methods to improve the quality of chest X-ray image have been studied in this paper. As the frequency domain filters work well for slight blurring and moderate levels of additive noises, we propose an algorithm that is particularly suitable for enhancing chest image. First, the chest image using Gaussian high pass filter and the optimal high frequency emphasis filter shows improvements in the edges and contrast of the flat areas. Second, as compared to using histogram equalization where each pixel of chest image is characterized by a loss of detail and much noises, in using fuzzy logic, each pixel of chest image shows the detail preservation and little noise.

• Journal of Advanced Marine Engineering and Technology
• /
• v.36 no.7
• /
• pp.919-926
• /
• 2012

In order to control a LTI(Linear Time Invariant) system subjected to system noise and measurement noise, first of all, it is necessary to estimate the state of system with reliability. Kalman filtering technique has been widely used to estimate the state of the stochastic LTI system with stationary noise characteristics because of its estimation ability versus algorithm simplicity. However, it often fails to estimate the state of the LTI system of which system parameter uncertainty exists partly and/or input uncertainty exists. In this paper, a new estimation technique based on Kalman filter is suggested for stochastic LTI system under parameter uncertainty and/or input uncertainty. A fuzzy estimation algorithm against uncertainties is introduced so as to compensate the state estimate filtered by Kalman filter. In order to verify the state estimation performance of the suggested technique, several simulations are accomplished.

• Journal of Power Electronics
• /
• v.12 no.5
• /
• pp.821-829
• /
• 2012

This research article presents a novel approach based on an instantaneous active and reactive power component (p-q) theory for generating reference currents for shunt active filter (SHAF). Three-phase reference current waveforms generated by proposed scheme are tracked by the three-phase voltage source converter in a hysteresis band control scheme. The performance of the SHAF using the p-q control strategy has been evaluated under various source conditions. The performance of the proposed control strategy has been evaluated in terms of harmonic mitigation and DC link voltage regulation. In order to maintain DC link voltage constant and to generate the compensating reference currents, we have developed Fuzzy logic controller with different (Trapezoidal, Triangular and Gaussian) fuzzy M.F.s. The proposed SHAF with different fuzzy M.F.s is able to eliminate the uncertainty in the system and SHAF gains outstanding compensation abilities. The detailed simulation results using MATLAB/SIMULINK software are presented to support the feasibility of proposed control strategy. To validate the proposed approach, the system is also implemented on a real time digital simulator and adequate results are reported for its verifications.