• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.133-135
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• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.

• Journal of the Korea Society for Simulation
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• v.23 no.2
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• pp.65-72
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• 2014

Sensor nodes are easily compromised by attacker when which are divided in open environment. The attacker may inject false report and false vote attack through compromised sensor node. These attacks interrupt to transmission legitimate report or the energy of sensor node is exhausted. PVFS are proposed by Li and Wu for countermeasure in two attacks. The scheme use inefficiency to energy of sensor node as fixed report threshold and verification node. In this paper, our propose the next neighbor node selection scheme based on fuzzy logic system for energy improvement of PVFS. The parameter of fuzzy logic system are energy, hops, verification success count, CH select high the next neighbor node among neighbor nodes of two as deduction based on fuzzy logic system. In the experimental, our proposed scheme was improvement to energy of about 9% compare to PVFS.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1625-1631
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• 2020

With the development of IoT technology, various digital equipment is being spread, and accordingly, the importance of data processing is increasing. The importance of data processing is increasing as it greatly affects the reliability of equipment, and various studies are being conducted. In this paper, we propose an algorithm to remove AWGN according to the characteristics of the fuzzy membership function. The proposed algorithm calculates the estimated value according to the correlation between the value of the fuzzy membership function between the input image and the pixel value inside the filtering mask, and obtains the final output by adding or subtracting the output of the spatial weight filter. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and analyzed using difference image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves the important characteristics of the image, and shows the performance of efficiently removing noise.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.363-371
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• 2010

In an effort to enhance the quality of feature vector classification and thereby reduce the recognition error rate for the speaker-independent speech recognition, we study the effect of spectral tilt on the Fourier magnitude spectrum en route to the extraction of MFCC. The effect of FIR filtering on the speech signal on the speech recognition is also investigated in parallel. Evaluation of the proposed methods are performed by two independent ways of the Fisher discriminant objective function and speech recognition test by hidden Markov model with fuzzy vector quantization. From the experiments, the recognition error rate is found to show about 10% relative improvements over the conventional method by an appropriate choice of the tilt factor.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.355-358
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• 2009

센서 네트워크에 대한 연구가 활발히 이루어지면서 센서 네트워크 보안에 대한 문제점이 많이 야기되고 있다. 무선 센서 네트워크에서는 개방된 환경에서 제한적인 자원을 가지는 노드들로 구성되어 있다. 개방된 환경에 배치된 노드들은 공격자에게 쉽게 노출되어질 수 있다. 공격자는 노드를 물리적으로 포획하여 데이터 인증에 사용하는 인증키와 같은 보안 정보들을 획득할 수 있다. 공격자는 포획된 노드를 통하여 허위 보고서로 무선 센서 네트워크에 쉽게 삽입시킬 수 있다. 이는 허위 보고서로 인한 혼란 및 위조 정보의 전달과정에서 발생하는 에너지 고갈 등의 문제점을 유발시키게 된다. 이러한 허위 보고서를 조기에 탐지 및 폐기하기 위하여 동적 여과 프로토콜(DEF: Dynamic En-route Filtering scheme)이 제안되었다. DEF에서 인증키를 재배포 하는 주기는 보안 강도와 비용을 트레이드-오프 하는 관계에 놓여있으므로 매우 중요하다. 본 논문에서는 센서네트워크에서 동적 여과 프로토콜의 인증키 재배포 주기를 결정하는 기법을 제안한다. 배포된 노드들의 위상변화, BS까지 도달한 허위보고서 비율, 공격자에게 포획된 노드의 수 등을 고려하여 재배포 여부를 결정하고 재배포가 결정되면 각 클러스터 헤드들에게 재배포를 명령하게 된다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.944-950
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• 2015

Recent studies on ankle-foot prostheses used for transtibial amputees have focused on the adaptation of the ankle angle of the prosthesis according to ground conditions. For adaptation to various ground conditions (e.g., incline, decline, and step conditions), ankle-foot prostheses should first recognize the ground conditions as well as the current human motion pattern. For this purpose, the ground reaction forces and orientation angle of the tibia provide fundamental information. The measurement of the orientation angle, however, creates a challenge in practice. Although various sensors, such as accelerometers and gyroscopes, can be utilized to measure the orientation angles of the prosthesis, none of these sensors can be solely used due to their intrinsic drawbacks. In this paper, a time-varying complementary filtering (TVCF) method is proposed to incorporate the measurements from an accelerometer and a gyroscope to obtain a precise orientation angle. The cut-off frequency of TVCF is adaptively determined according to the human gait phase detected by a fuzzy logic algorithm. The performance of the proposed method is verified through experiments.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1004-1019
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• 2021

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.125-131
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• 2010

In wireless sensor networks application, sensor nodes are randomly deployed in wide and opened environment typically. Since sensor networks have these features, it is vulnerable to physical attacks in which an adversary can capture deployed nodes and use them to inject a fabricated report into the network. This threats of network security deplete the limited energy resource of the entire network using injected fabricated reports. A dynamic en-route filtering scheme is proposed to detect and drop the injected fabricated report. In this scheme, node executes the key redistribution to increases the detection power. It is very important to decide the authentication key redistribution because a frequent key redistribution can cause the much energy consumption of nodes. In this paper, we propose a key redistribution determining method to enhance the energy efficiency and maintain the detection power of network. Each node decides the authentication key redistribution using a fuzzy system in a definite period. The proposed method can provide early detection of fabricated reports, which results in energy-efficiency against the massive fabricated report injection attacks.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.53-61
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• 2010

In wireless sensor networks(WSNs) individual sensor nodes are subject to security compromises. An adversary can physically capture sensor nodes and obtain the security information. And the adversary injects false reports into the network using compromised nodes. If undetected, these false reports are forwarded to the base station. False reports injection attacks can not only result in false alarms but also depletion of the limited amount of energy in battery powered sensor nodes. To combat these false reports injection attacks, several filtering schemes have been proposed. The statistical en-routing filtering(SEF) scheme can detect and drop false reports during the forwarding process. In SEF, The number of the message authentication codes(threshold) is important for detecting false reports and saving energy. In this paper, we propose a dynamic threshold determination method for energy efficient SEF using fuzzy-logic in wireless sensor networks. The proposed method consider false reports rate and the number of compromised partitions. If low rate of false reports in the networks, the threshold should low. If high rate of false reports in networks, the threshold should high. We evaluated the proposed method’s performance via simulation.