• Title/Summary/Keyword: descriptor systems

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Region-based Shape Descriptor with Moving a Vision Center for Image Representation (영상표현을 위한 비전 중심점 이동에 따른 영역기반 형태 기술자)

  • Kim Seon-Jong;Kim Young-In
    • Journal of Intelligence and Information Systems
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    • v.12 no.1
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    • pp.95-105
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    • 2006
  • This paper proposes a novel approach to represent the image by using shape descriptor having an information of area. The proposed descriptor is a set of vectors, consists of radius, area and direction parameters in the concentrated center point. Due to the area parameter, we know our descriptor can obtain the information of area. Also, we give an extended shape descriptor to get more detailed representation. To do this, we move the center point of our vision to that point for region of interest. By doing so about all of region of interest, we can get our descriptor for detailed information of the image. From more detailed descriptor, it's natural that it's more efficient fur representation, retrievals and so on. We make it the normalized pattern and expand to improve its quality. The proposed method is invariant to scale, position and rotation. The results show that it can be used efficiently for image representation as we can see in retrievals of silhouette images.

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A Multiple Features Video Copy Detection Algorithm Based on a SURF Descriptor

  • Hou, Yanyan;Wang, Xiuzhen;Liu, Sanrong
    • Journal of Information Processing Systems
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    • v.12 no.3
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    • pp.502-510
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    • 2016
  • Considering video copy transform diversity, a multi-feature video copy detection algorithm based on a Speeded-Up Robust Features (SURF) local descriptor is proposed in this paper. Video copy coarse detection is done by an ordinal measure (OM) algorithm after the video is preprocessed. If the matching result is greater than the specified threshold, the video copy fine detection is done based on a SURF descriptor and a box filter is used to extract integral video. In order to improve video copy detection speed, the Hessian matrix trace of the SURF descriptor is used to pre-match, and dimension reduction is done to the traditional SURF feature vector for video matching. Our experimental results indicate that video copy detection precision and recall are greatly improved compared with traditional algorithms, and that our proposed multiple features algorithm has good robustness and discrimination accuracy, as it demonstrated that video detection speed was also improved.

Robust $H_\infty$ Output Feedback Control of Descriptor Systems with Parameter Uncertainty and Time dDelay (파라미터 불확실성과 시간지연을 가지는 특이시스템의 견실 $H_\infty$ 출력궤환 제어)

  • 김종해
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.41 no.3
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    • pp.9-16
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    • 2004
  • This paper provides an observer-based Η$\infty$ output feedback controller design method for descriptor systems with time-varying delay by just one LMI(linear matrix inequality) condition. The sufficient condition for the existence of controller and the controller design method are presented by perfect LMI approach which can be solved efficiently by convex optimization. The design procedure involves solving an LMI. Since the obtained condition can be expressed as an LMI form all variables including feedback gain and observer gain can be calculated simultaneously by Schur complement changes of variables, and singular value decomposition. Moreover, The proposed controller design algorithm can be extended to the observer-based robust Η$\infty$ output feedback controller design method for descriptor systems with parameter uncertainty and time delay. An example is given to illustrate the results.

Non-fragile robust guaranteed cost control for descriptor systems with parameter uncertainties (변수 불확실성 특이시스템의 비약성 강인 보장비용 제어)

  • Kim, Jong-Hae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.1
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    • pp.59-66
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    • 2007
  • In this paper, we consider the non-fragile robust guaranteed cost state feedback controllers design method for descriptor systems with parameter uncertainties and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile robust guaranteed cost controller, the measure of non-fragility in controller, the upper bound of guaranteed cost performance measure to minimize the guaranteed cost are presented via LMI(linear matrix inequality) technique. Also, the sufficient condition can be rewritten as LMI form in terms of transformed variables through singular value decomposition, some changes of variables, and Schur complements. Therefore, the obtained non-fragile robust guaranteed cost controller satisfies the asymptotic stability and minimizes the guaranteed cost for the closed loop descriptor systems with parameter uncertainties and controller fragility. Finally, a numerical example is given to illustrate the design method.

Robust and Non-fragile $H_{\infty}$ Control for Descriptor Systems with Parameter Uncertainties and Time Delay

  • Kim, Jong-Hae;Oh, Do-Chang
    • International Journal of Control, Automation, and Systems
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    • v.5 no.1
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    • pp.8-14
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    • 2007
  • This paper describes a robust and non-fragile $H_{\infty}$ controller design method for descriptor systems with parameter uncertainties and time delay, as well as a static state feedback controller with multiplicative uncertainty. The controller existence condition, as well as its design method, and the measure of non-fragility in the controller are proposed using linear matrix inequality(LMI) technique, which can be solved efficiently by convex optimization. Therefore, the presented robust and non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop systems within a prescribed degree in spite of parameter uncertainties, time delay, disturbance input and controller fragility.

RLDB: Robust Local Difference Binary Descriptor with Integrated Learning-based Optimization

  • Sun, Huitao;Li, Muguo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.9
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    • pp.4429-4447
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    • 2018
  • Local binary descriptors are well-suited for many real-time and/or large-scale computer vision applications, while their low computational complexity is usually accompanied by the limitation of performance. In this paper, we propose a new optimization framework, RLDB (Robust-LDB), to improve a typical region-based binary descriptor LDB (local difference binary) and maintain its computational simplicity. RLDB extends the multi-feature strategy of LDB and applies a more complete region-comparing configuration. A cascade bit selection method is utilized to select the more representative patterns from massive comparison pairs and an online learning strategy further optimizes descriptor for each specific patch separately. They both incorporate LDP (linear discriminant projections) principle to jointly guarantee the robustness and distinctiveness of the features from various scales. Experimental results demonstrate that this integrated learning framework significantly enhances LDB. The improved descriptor achieves a performance comparable to floating-point descriptors on many benchmarks and retains a high computing speed similar to most binary descriptors, which better satisfies the demands of applications.

Delay-dependent Stabilization of Singular Systems with Multiple Internal and External Incommensurate Constant Point Delays

  • Xie, Yong-Fang;Gui, Wei-Hua;Jiang, Zhao-Hui
    • International Journal of Control, Automation, and Systems
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    • v.6 no.4
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    • pp.515-525
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    • 2008
  • In this paper, the problem of delay-dependent stabilization for singular systems with multiple internal and external incommensurate constant point delays is investigated. The condition when a singular system subject to point delays is regular independent of time delays is given and it can be easily test with numerical or algebraic methods. Based on Lyapunov-Krasovskii functional approach and the descriptor integral-inequality lemma, a sufficient condition for delay-dependent stability is obtained. The main idea is to design multiple memoryless state feedback control laws such that the resulting closed-loop system is regular independent of time delays, impulse free, and asymptotically stable via solving a strict linear matrix inequality (LMI) problem. An explicit expression for the desired memoryless state feedback control laws is also given. Finally, a numerical example illustrates the effectiveness and the availability for the proposed method.

Robust Passive Low-order Filtering for Discrete-time Uncertain Descriptor Systems (이산시간 불확실 특이시스템의 저차 강인 피동성 필터링)

  • Kim, Jong-Hae;Oh, Do-Cang
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.3
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    • pp.466-471
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    • 2012
  • In this paper, we consider the problem of a robust passive filtering with low-order for discrete-time singular systems with polytopic uncertainties. A BRL(bounded real lemma) for robust passivity with a dissipativity of discrete-time uncertain singular systems is derived. A low-order robust passive filter design method is proposed by new reduced-order method and LMI(linear matrix inequality) technique on the basis of the obtained BRL. Finally, illustrative examples are presented to show the applicability of the proposed method.

Two-degree-of-freedom control for descriptor system with disturbance

  • Yeu, Tae-Kyeong;Kawaji, Shigeyasu
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.151.2-151
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    • 2001
  • In this paper, the design of a two-degree-of-freedom(TDF) controller is proposed to track the reference model, as well as to reject an influence of measurable disturbance for descrpitor system. The TDF controllers based on the Youla parametrization reveals that the design of the feedforward controller and the regulator can be done independently. First, to solve this problem, we will change descriptor system into regular state space system using a state feedback. And then, the feedforward controller is determined by solving a full information approach for augmented system with a nominal control constraint, and the regulator is designed by means of the loop-Shaping method.

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The Implementation of Fast Object Recognition Using Parallel Processing on CPU and GPU (CPU와 GPU의 병렬 처리를 이용한 고속 물체 인식 알고리즘 구현)

  • Kim, Jun-Chul;Jung, Young-Han;Park, Eun-Soo;Cui, Xue-Nan;Kim, Hak-Il;Huh, Uk-Youl
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.5
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    • pp.488-495
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    • 2009
  • This paper presents a fast feature extraction method for autonomous mobile robots utilizing parallel processing and based on OpenMP, SSE (Streaming SIMD Extension) and CUDA programming. In the first step on CPU version, the algorithms and codes are optimized and then implemented by parallel processing. The parallel algorithms are debugged to maintain the same level of performance and the process for extracting key points and obtaining dominant orientation with respect to key points is parallelized. After extraction, a parallel descriptor via SSE instructions is constructed. And the GPU version also implemented by parallel processing using CUDA based on the SIFT. The GPU-Parallel descriptor achieves an acceleration up to five times compared with the CPU-Parallel descriptor, but it shows the lower performance than CPU version. CPU version also speed-up the four and half times compared with the original SIFT while maintaining robust performance.