• Title/Summary/Keyword: Robot Control

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Noise Removal Algorithm based on Fuzzy Membership Function in AWGN Environments (AWGN 환경에서 퍼지 멤버십 함수에 기반한 잡음 제거 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • 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.

Digital Filter Algorithm based on Mask Matching for Image Restoration in AWGN Environment (AWGN 환경에서 영상복원을 위한 마스크매칭 기반의 디지털 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.2
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    • pp.214-220
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    • 2021
  • In modern society, various digital communication equipments are being used due to the influence of the 4th industrial revolution, and accordingly, interest in removing noise generated in the data transmission process is increasing. In this paper, we propose a filtering algorithm to remove AWGN generated during digital image transmission. The proposed algorithm removes noise based on mask matching to preserve information such as the boundary of an image, and uses pixel values with similar patterns according to the pattern of the input pixel value and the surrounding pixels for output calculation. To evaluate the proposed algorithm, we simulated with existing AWGN removal algorithms, and analyzed using enlarged image and PSNR comparison. The proposed algorithm has superior AWGN removal performance compared to the existing method, and is particularly effective in images with strong noise intensity of AWGN.

Development of Functional Auxiliary Device to Improve Induction Safety (인덕션 안전성 향상을 위한 기능보조 디바이스 개발)

  • Kim, Min-Kyoung;Seo, Dong-Min;Yoo, Dong-Hun;Yoo, Jin-Young;Jeong, Seong-Ho;Choi, Heon-Soo;Baek, Soo-Whang
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1263-1270
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    • 2021
  • Recently, in the food culture life, the trend of consumers cooking is changing, and the use rate of induction cookware is increasing. Therefore, in this study, we propose the development of a functional auxiliary device to improve the safety of induction cookware to improve the convenience of cooking according to the increase in the cooking population. The proposed device is linked with IoT through the app. Through the app, the device can control the induction heating power adjustment and time reservation. In addition, an ultrasonic sensor is used to prevent the container from overflowing during cooking, and the user can safely use induction through the fine dust sensor. The implemented device conducts research assuming the actual cooking situation. Finally, it was confirmed that the user's fatigue was reduced during cooking through the device and the user's safety was improved in emergency situations such as overcooking or overflowing of water.

Analysis of the Valuation Model for the state-of-the-art ICT Technology (첨단 ICT 기술에 대한 가치평가 모델 분석)

  • Oh, Sun-Jin
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.705-710
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    • 2021
  • Nowadays, cutting-edge information communication technology is the genuine core technology of the fourth Industrial Revolution and is still making great progress rapidly among various technology fields. The biggest issue in ICT fields is the machine learning based Artificial Intelligence applications using big data in cloud computing environment on the basis of wireless network, and also the technology fields of autonomous control applications such as Autonomous Car or Mobile Robot. Since value of the high-tech ICT technology depends on the surrounded environmental factors and is very flexible, the precise technology valuation method is urgently needed in order to get successful technology transfer, transaction and commercialization. In this research, we analyze the characteristics of the high-tech ICT technology and the main factors in technology transfer or commercialization process, and propose the precise technology valuation method that reflects the characteristics of the ICT technology through phased analysis of the existing technology valuationmodel.

Digital Filter Algorithm based on Local Steering Kernel and Block Matching in AWGN Environment (AWGN 환경에서 로컬 스티어링 커널과 블록매칭에 기반한 디지털 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.7
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    • pp.910-916
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    • 2021
  • In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR.

Efficient Visual Place Recognition by Adaptive CNN Landmark Matching

  • Chen, Yutian;Gan, Wenyan;Zhu, Yi;Tian, Hui;Wang, Cong;Ma, Wenfeng;Li, Yunbo;Wang, Dong;He, Jixian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.4084-4104
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    • 2021
  • Visual place recognition (VPR) is a fundamental yet challenging task of mobile robot navigation and localization. The existing VPR methods are usually based on some pairwise similarity of image descriptors, so they are sensitive to visual appearance change and also computationally expensive. This paper proposes a simple yet effective four-step method that achieves adaptive convolutional neural network (CNN) landmark matching for VPR. First, based on the features extracted from existing CNN models, the regions with higher significance scores are selected as landmarks. Then, according to the coordinate positions of potential landmarks, landmark matching is improved by removing mismatched landmark pairs. Finally, considering the significance scores obtained in the first step, robust image retrieval is performed based on adaptive landmark matching, and it gives more weight to the landmark matching pairs with higher significance scores. To verify the efficiency and robustness of the proposed method, evaluations are conducted on standard benchmark datasets. The experimental results indicate that the proposed method reduces the feature representation space of place images by more than 75% with negligible loss in recognition precision. Also, it achieves a fast matching speed in similarity calculation, satisfying the real-time requirement.

Switching Filter Algorithm using Fuzzy Weights based on Gaussian Distribution in AWGN Environment (AWGN 환경에서 가우시안 분포 기반의 퍼지 가중치를 사용한 스위칭 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.207-213
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    • 2022
  • Recently, with the improvement of the performance of IoT technology and AI, automation and unmanned work are progressing in a wide range of fields, and interest in image processing, which is the basis of automation such as object recognition and object classification, is increasing. Image noise removal is an important process used as a preprocessing step in an image processing system, and various studies have been conducted. However, in most cases, it is difficult to preserve detailed information due to the smoothing effect in high-frequency components such as edges. In this paper, we propose an algorithm to restore damaged images in AWGN(additive white Gaussian noise) using fuzzy weights based on Gaussian distribution. The proposed algorithm switched the filtering process by comparing the filtering mask and the noise estimate with each other, and reconstructed the image by calculating the fuzzy weights according to the low-frequency and high-frequency components of the image.

AWGN Removal using Laplace Distribution and Weighted Mask (라플라스 분포와 가중치 마스크를 이용한 AWGN 제거)

  • Park, Hwa-Jung;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.12
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    • pp.1846-1852
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    • 2021
  • In modern society, various digital devices are being distributed in a wide range of fields due to the fourth industrial revolution and the development of IoT technology. However, noise is generated in the process of acquiring or transmitting an image, and not only damages the information, but also affects the system, causing errors and incorrect operation. AWGN is a representative noise among image noise. As a method for removing noise, prior research has been conducted, and among them, AF, A-TMF, and MF are the representative methods. Existing filters have a disadvantage that smoothing occurs in areas with high frequency components because it is difficult to consider the characteristics of images. Therefore, the proposed algorithm calculates the standard deviation distribution to effectively eliminate noise even in the high frequency domain, and then calculates the final output by applying the probability density function weight of the Laplace distribution using the curve fitting method.

Analysis of the Image Processing Speed by Line-Memory Type (라인메모리 유형에 따른 이미지 처리 속도의 분석)

  • Si-Yeon Han;Semin Jung;Bongsoon Kang
    • Journal of IKEEE
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    • v.27 no.4
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    • pp.494-500
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    • 2023
  • Image processing is currently used in various fields. Among them, autonomous vehicles, medical image processing, and robot control require fast image processing response speeds. To fulfill this requirement, hardware design for real-time processing is being actively researched. In addition to the size of the input image, the hardware processing speed is affected by the size of the inactive video periods that separate lines and frames in the image. In this paper, we design three different scaler structures based on the type of line memories, which is closely related to the inactive video periods. The structures are designed in hardware using the Verilog standard language, and synthesized into logic circuits in a field programmable gate array environment using Xilinx Vivado 2023.1. The synthesized results are used for frame rate analysis while comparing standard image sizes that can be processed in real time.

A Optimization Study of UAV Path Planning Generation based-on Rapid-exploring Random Tree Method (급속탐색랜덤트리기법 기반의 무인 비행체 경로계획생성 최적화 연구)

  • Jae-Hwan Bong;Seong-Kyun Jeong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.5
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    • pp.981-988
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    • 2023
  • As the usage of unmanned aerial vehicles expands, the development and the demand of related technologies are increasing. As the frequency of operation increases and the convenience of operation is emphasized, the importance of related autonomous flight technology is also highlighted. Establishing a path plan to reach the destination in autonomous flight of an unmanned aerial vehicle is important in guidance and control, and a technology for automatically generating path plan is required in order to maximize the effect of unmanned aerial vehicle. In this study, the optimization research of path planning using rapid-exploring random tree method was performed for increasing the effectiveness of autonomous operation. The path planning optimization method considering the characteristics of the unmanned aerial vehicle is proposed. In order to achieve indexes such as optimal distance, shortest time, and passage of mission points, the path planning was optimized in consideration of the mission goals and dynamic characteristics of the unmanned aerial vehicle. The proposed methods confirmed their applicability to the generation of path planning for unmanned aerial vehicles through performance verification for obstacle situations.