• Title/Summary/Keyword: 구역필터 알고리즘

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Development of Position Awareness Algorithm Using Improved Trilateration Measurement Method (개선된 삼변측량법을 이용한 위치인지 알고리즘 개발)

  • Sohn, Jong-Hoon;Hwang, Gi-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.2
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    • pp.473-480
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    • 2013
  • In this paper, location recognition algorithm is developed to improve the accuracy using improve Trilateration. The location recognition algorithm is first calculate the location refer to the measured signal power. Error can be occurred when measure distance with arranged node in specific location. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. Second, we apply algorithm of section filtering. If there are 4 sections in node, we consider 1 section to 6 location recognition coordinates. A special characteristic drawback of RF is that the actual distance is actually farther than the calculated received distance data. This is error is incurred when the signal strength increases. We reduce the location recognition error by applying an improved algorithm as secondary after filtering primary through section filtering.

Image Enhancement Using Adaptive Weighted Sigma Filter (적응비중화 시그마필터에 의한 영상향상)

  • Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.2 s.314
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    • pp.19-26
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    • 2007
  • In the sigma filter, there is a specialized neighbours distribution scheme in which the sigma value is computed from local statistics. It is designed to modify a standard average filter to preserve edges. However this filter is vulnerable to details-enhancement and conventional sigma approaches have been focused on denoising, not enhancing the characteristic area. This paper proposes an adaptive image enhancement algorithm using local statistics and functional synthesis which are utilized for adaptive realization of the enhancement, so that not only image noise may be smoothed but also details may be enhanced. For the local adaptation, parameters are estimated and weighted at each moving window that satisfy the criteria. The experimental results illuminates the effectiveness of the proposed method.

Multiple Moving Object Tracking Using The Background Model and Neighbor Region Relation (배경 모델과 주변 영역과의 상호관계를 이용한 다중 이동 물체 추적)

  • Oh, Jeong-Won;Yoo, Ji-Sang
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.4
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    • pp.361-369
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    • 2002
  • In order to extract motion features from an input image acquired by a static CCD-camera in a restricted area, we need a robust algorithm to cope with noise sensitivity and condition change. In this paper, we proposed an efficient algorithm to extract and track motion features in a noisy environment or with sudden condition changes. We extract motion features by considering a change of neighborhood pixels when moving objects exist in a current frame with an initial background. To remove noise in moving regions, we used a morphological filter and extracted a motion of each object using 8-connected component labeling. Finally, we provide experimental results and statistical analysis with various conditions and models.

A design and implementation of Intelligent object recognition system in urban railway (도시철도내 지능형 객체인식 시스템 구성 및 설계)

  • Park, Ho-Sik
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.2
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    • pp.209-214
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    • 2018
  • The subway, which is an urban railway, is the core of public transportation. Urban railways are always exposed to serious problems such as theft, crime and terrorism, as many passengers use them. Especially, due to the nature of urban railway environment, the scope of surveillance is widely dispersed and the range of surveillance target is rapidly increasing. Therefore, it is difficult to perform comprehensive management by passive surveillance like existing CCTV. In this paper, we propose the implementation, design method and object recognition algorithm for intelligent object recognition system in urban railway. The object recognition system that we propose is to analyze the camera images in the history and to recognize the situations where there are objects in the landing area and the waiting area that are not moving for more than a certain time. The proposed algorithm proved its effectiveness by showing detection rate of 100% for Selected area detection, 82% for detection in neglected object, and 94% for motionless object detection, compared with 84.62% object recognition rate using existing Kalman filter.

Multibeam-based Subspace Approach for Code Acquisition in Antenna Array DS-CDMA Systems (안테나 어레이 DS-CDMA 통신 시스템에서 코드 동기 획득을 위한 다중 빔 기반의 부분공간 접근 방법)

  • Kim, Sang-Choon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.6
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    • pp.1167-1173
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    • 2005
  • In this paper, the use of an antenna array is considered for code timing acquisition of DS-CDMA signals. The probabilities of acquisition are evaluated by applying multiple narrow fixed-beams to the conventional MUSIC acquisition approach in the multiuser environment on the time-varying Rayleigh fading channel. Each fixed-beam for spatial filtering is dedicated to an individual angular sector that is formed by dividing the entire angular domain by the number of antenna elements. The fixed-beams with a capability of interference suppression provide the additional degrees of freedom,. Hence, the multibeam-based MUSIC estimator can be used to synchronize to more users than the conventional MUSIC algorithm for one antenna. The multibeam-based subspace method is evaluated to significantly improve the performance of a single antenna based MUSIC technique in multiuser scenarios.

Connectivity Verification and Noise Reduction Analysis of Smart Safety Helmet for Shipyard Worker (조선소 작업자를 위한 스마트 안전모의 커넥티비티 검증 및 소음저감 분석)

  • Park, Junhyeok;Heo, Junyeoung;Lee, Sangbok;Park, Jaemun;Park, Jun-Soo;Lee, Kwangkook
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.1
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    • pp.28-36
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    • 2022
  • Currently, the automation and intelligence of the shipbuilding industry have improved its work production capacity and cost competitiveness, but the reduction rate of safety accidents among industrial site workers is still low and the damage caused by safety accidents is very serious, so there is a need for improvement according to the workplace. This research aims to demonstrate the connectivity between smart safety helmets in the demonstration area to verify the effectiveness along with the development of smart helmets for worker protection and environmental safety in shipyards. For efficient communication between workers, impact noise of over 95dB was confirmed in the workplace, and noise reduction was required. To solve this problem, the filtering performance was compared and analyzed using the Butterworth, Chebyshev, and elliptic algorithms. The connectivity test and noise reduction method between smart helmets proposed in this study will increase the usability and safety of the field through the development of advanced smart helmets tailored to the shipbuilding workplace in the future.