• 제목/요약/키워드: Real-time Filtering

검색결과 430건 처리시간 0.035초

스마트폰에서 이미지 필터링 효과의 직관적 조정을 위한 내장센서의 적용 기법 (A Technique of Applying Embedded Sensors to Intuitive Adjustment of Image Filtering Effect in Smart Phone)

  • 김지연;권석민;정종진
    • 한국멀티미디어학회논문지
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    • 제18권8호
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    • pp.960-967
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    • 2015
  • In this paper, we propose a user interface technique based on embedded sensors applying to apps in smart phone. Especially, we implement avata generation application using image filtering technique for photo image in smart phone. In the application, The embedded sensors are used as intuitive user interface to adjust the image filtering effect for making user satisfied effect in real time after the system produced the image filtering effect for avatar. This technique provides not a simple typed method of parameter values adjustment but a new intuitively emotional adjustment method in image filtering applications. The proposed technique can use sound values from embedded mike sensor for adjusting key values of sketch filter effect if the smart phone user produces sound. Similiarly the proposed technique can use coordinate values from embedded acceleration sensor for adjusting masking values of oil painting filter effect and use brightness values from embedded light sensor for adjusting masking values of sharp filter effect. Finally, we implement image filtering application and evaluate efficiency and effectiveness for the proposed technique.

적응형 필터링 기법을 이용한 회전형 시선제어시스템의 진동 저감 및 영상 주파수노이즈 저감 기법 (An Adaptive Filtering Technique for Vibration Reduction of a Rotational LOS Control System and Frequency Noise Reduction of an Imaging System)

  • 김병학;김민영
    • 제어로봇시스템학회논문지
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    • 제20권10호
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    • pp.1014-1022
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    • 2014
  • In mechatronic systems using electric signals to drive control systems, driving signals including the frequency band of the unwanted signals, such as resonant frequencies and noise frequencies, can affect the accuracy of the controlled system and can cause serious damage to the system due to the resonance phenomenon of the mechatronic system. An LOS (Line of Sight) control unit is used to automatically rotate the gimbal system with a video imaging system generally mounted on modern aerial vehicles. However, it still suffers from natural frequency variation problems due to variations of operational temperature. To prevent degradation in performance, this paper proposes an adaptive filtering technique based on real-time noise analysis and adaptive notch-filtering for LOS control systems, and verifies how our proposed method maintains the LOS stabilization performance. Additionally, this filtering technique can be applied to the image noise filtering of the video imaging system. It is designed to reduce image noises generated by switching circuits or power sources. The details of design procedures of the proposed filtering technique and the experiments for the performance verification are described in this paper.

고속 병렬 패킷 여과를 위한 효율적인 단일버퍼 관리 방안 (An Efficient Central Queue Management Algorithm for High-speed Parallel Packet Filtering)

  • 임강빈;박준구;최경희;정기현
    • 대한전자공학회논문지TC
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    • 제41권7호
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    • pp.63-73
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    • 2004
  • 본 논문은 고속의 병렬 패킷 여과를 위한 다중프로세서 시스템이 가지는 단일 버퍼에서 단일 버퍼의 판독을 위한 다중프로세서 간의 경합을 중재하기 위한 효율적인 단일 버퍼 관리 방안을 제안하고 이를 실제의 다중 프로세서 시스템에 적용하여 실험함으로써 제안한 방안이 납득할 만한 성능을 제공함을 증명하였다. 병렬 패킷 여과시스템으로는 처리의 고속화를 위하여 패킷 여과규칙을 다중의 프로세서에 걸쳐 분산 처리하는 경우를 모델로 정하였다. 실제의 실험은 다중 프로세서를 가지는 네트워크 프로세서에서 이루어졌으며 100Mbps 의 통신망을 배경으로 하였다. 제안한 방안의 성능을 고찰하기 위하여 프로세서 수의 변화 및 여과 규칙의 처리 시간의 변화 등에 따르는 실제 패킷 전송률을 측정하였다.

A Fast Algorithm for Real-time Adaptive Notch Filtering

  • Kim, Haeng-Gihl
    • Journal of information and communication convergence engineering
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    • 제1권4호
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    • pp.189-193
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    • 2003
  • A new algorithm is presented for adaptive notch filtering of narrow band or sine signals for embedded among broad band noise. The notch filter is implemented as a constrained infinite impulse response filter with a minimal number of parameters, Based on the recursive prediction error (RPE) method, the algorithm has the advantages of the fast convergence, accurate results and initial estimate of filter coefficient and its covariance is revealed. A convergence criterion is also developed. By using the information of the noise-to-signal power, the algorithm can self-adjust its initial filter coefficient estimate and its covariance to ensure convergence.

증류공정의 차수감소모델 개발 및 비선형휠터기법을 이용한 모델인식에 관한 연구 (A study on development of a reduced-order distillation model and identification using nonlinear filtering techniques)

  • 김홍식;이광순
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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    • pp.367-371
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    • 1989
  • A linear form of reduced-order distillation model is proposed, which contains the physical properties of distillation process and can be used in real time applications. The proposed model is linear in terms of liquid mole fraction and contains some tuning parameters. To verify the applicability of the proposed model, the model identification using nonlinear filtering techniques was applied. As a result, it was found that this model represented the simulated distillation process very closely as the parameters were converged.

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Recursive Unscented Kalman Filtering based SLAM using a Large Number of Noisy Observations

  • Lee, Seong-Soo;Lee, Suk-Han;Kim, Dong-Sung
    • International Journal of Control, Automation, and Systems
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    • 제4권6호
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    • pp.736-747
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    • 2006
  • Simultaneous Localization and Map Building(SLAM) is one of the fundamental problems in robot navigation. The Extended Kalman Filter(EKF), which is widely adopted in SLAM approaches, requires extensive computation. The conventional particle filter also needs intense computation to cover a high dimensional state space with particles. This paper proposes an efficient SLAM method based on the recursive unscented Kalman filtering in an environment including a large number of landmarks. The posterior probability distributions of the robot pose and the landmark locations are represented by their marginal Gaussian probability distributions. In particular, the posterior probability distribution of the robot pose is calculated recursively. Each landmark location is updated with the recursively updated robot pose. The proposed method reduces filtering dimensions and computational complexity significantly, and has produced very encouraging results for navigation experiments with noisy multiple simultaneous observations.

Post-Processing for Reducing Blocking Artifacts using Adaptive Low Pass Filtering

  • Hwang, Younghooi;Jeon, Byeungwoo;Sull, Sanghoon
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.297-300
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    • 2002
  • In this paper, we propose a post-processing method to reduce the blocking artifacts. We perform the post-processing only in the spatial domain so that it is readily applicable to real-time video decoder. Many approaches proposed so far for deblocking deal with only The luminance signal. but here we propose processing the chrominance signals as well since the low bit rare application where the blocking artifacts are most problematic suffers significantly from the color misalignment caused by blocking artifacts occurring to chrominance data as well. The proposed method is composed of low pass filtering in two steps considering the edge direction. The first step is the IIR low pass filtering in the diagonal direction, and the second step is another IIR low pass filtering in horizontal and vertical directions.

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R-필터링을 이용한 자동차 브레이크등 검출과 인식 (Detection and Recognition of Vehicle Brake Lights using an R-Filtering)

  • 정민철
    • 반도체디스플레이기술학회지
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    • 제10권4호
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    • pp.95-100
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    • 2011
  • This paper proposes a new method of vehicle brake lights detection and recognition using an R-filtering. Firstly, the proposed method processes the R-filtering with the first input image and then with the second one in order to detect brake lights. Secondly, the method counts the number of red pixels and computes the mean value in each R-filtered image. The difference rates between the numbers of the red pixels and between the mean values of two images are defined in this paper. Through the analysis of the difference rates, it can recognize whether brake lights are turned on or off, and whether the vehicle ahead is being approached or not. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithm is quite successful.

Integration of User Profiles and Real-time Context Information Reflecting Time-based Changes for the Recommendation System

  • Lee, Se-Il;Lee, Sang-Yong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권4호
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    • pp.270-275
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    • 2008
  • Under ubiquitous environment, recommendation system is using the collaborative filtering methods by quantifying context information, but insufficient context information can cause inaccurate recommendation result. In order to solve such problems, the researcher used context information and user's profile. But service history information in users' profiles can have the problems of being influenced by change of the user's taste or fashion as time passes by. In addition, context information and user's profile can't be properly inter-locked according to situation, which can cause inaccurate predictability. In this paper, in case a user's taste or fashion is changed as time passes by, the researcher didn't apply bundled-up value to the user's profile but applied different weight according to change of time. And the researcher could solve the problem that context information and a user's profile can't be properly inter-locked according to situation by applying different weight to the result gained by means of collaborative filtering and then by unifying it. In such ways, the researcher could improve predictability.

A Cascade-hybrid Recommendation Algorithm based on Collaborative Deep Learning Technique for Accuracy Improvement and Low Latency

  • Lee, Hyun-ho;Lee, Won-jin;Lee, Jae-dong
    • 한국멀티미디어학회논문지
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    • 제23권1호
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    • pp.31-42
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    • 2020
  • During the 4th Industrial Revolution, service platforms utilizing diverse contents are emerging, and research on recommended systems that can be customized to users to provide quality service is being conducted. hybrid recommendation systems that provide high accuracy recommendations are being researched in various domains, and various filtering techniques, machine learning, and deep learning are being applied to recommended systems. However, in a recommended service environment where data must be analyzed and processed real time, the accuracy of the recommendation is important, but the computational speed is also very important. Due to high level of model complexity, a hybrid recommendation system or a Deep Learning-based recommendation system takes a long time to calculate. In this paper, a Cascade-hybrid recommended algorithm is proposed that can reduce the computational time while maintaining the accuracy of the recommendation. The proposed algorithm was designed to reduce the complexity of the model and minimize the computational speed while processing sequentially, rather than using existing weights or using a hybrid recommendation technique handled in parallel. Therefore, through the algorithms in this paper, contents can be analyzed and recommended effectively and real time through services such as SNS environments or shared economy platforms.