MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

Considers the problems of robust stability and stabilization for uncertain continuous singular systems with state delay. The parametric uncertainty is assumed to be norm bounded. The purpose of the robust stability problem is to give conditions such that the uncertain singular system is regular, impulse free, and stable for all admissible uncertainties, while the purpose of the robust stabilization is to design a state feedback control law such that the resulting closed-loop system is robustly stable. These problems are solved via the notions of generalized quadratic stability and generalized quadratic stabilization, respectively. Necessary and sufficient conditions for generalized quadratic stability and generalized quadratic stabilization are derived. A strict linear matrix inequality (LMI) design approach is developed. An explicit expression for the desired robust state feedback control law is also given. Finally, a numerical example is provided to demonstrate the application of the proposed method.

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Robust stability and stabilization for singular systems with state delay and parameter uncertainty

Asymptotically necessary and sufficient conditions for stability and performance in fuzzy control: Applications of Polya's theorem

This paper presents the stability analysis of interval type-2 fuzzy-model-based (FMB) control systems. To investigate the system stability, an interval type-2 Takagi-Sugeno (T-S) fuzzy model, which can be regarded as a collection of a number of type-1 T-S fuzzy models, is proposed to represent the nonlinear plant subject to parameter uncertainties. With the lower and upper membership functions, the parameter uncertainties can be effectively captured. Based on the interval type-2 T-S fuzzy model, an interval type-2 fuzzy controller is proposed to close the feedback loop. To facilitate the stability analysis, the information of the footprint of uncertainty is used to develop some membership function conditions, which allow the introduction of slack matrices to handle the parameter uncertainties in the stability analysis. Stability conditions in terms of linear matrix inequalities are derived using a Lyapunov-based approach. Simulation examples are given to illustrate the effectiveness of the proposed interval type-2 FMB control approach.

Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems

This paper investigates the problem of output feedback robust $\mathscr{H}_{\infty }$ control for a class of nonlinear spatially distributed systems described by first-order hyperbolic partial differential equations (PDEs) with Markovian jumping actuator faults. The nonlinear hyperbolic PDE systems are first expressed by Takagi–Sugeno fuzzy models with parameter uncertainties, and then, the objective is to design a reliable distributed fuzzy static output feedback controller guaranteeing the stochastic exponential stability of the resulting closed-loop system with certain $\mathscr{H}_{\infty }$ disturbance attenuation performance. Based on a Markovian Lyapunov functional combined with some matrix inequality convexification techniques, two approaches are developed for reliable fuzzy static output feedback controller design of the underlying fuzzy PDE systems. It is shown that the controller gains can be obtained by solving a set of finite linear matrix inequalities based on the finite-difference method in space. Finally, two examples are presented to demonstrate the effectiveness of the proposed methods.

Fuzzy-Model-Based Reliable Static Output Feedback $\mathscr{H}_{\infty }$ Control of Nonlinear Hyperbolic PDE Systems

This study proposed an off-line method to quantitively analyze the dosimetric impact of daily setup variations on Intensity-modulated radiotherapy (IMRT) when these variations are not corrected due to the lack of image guidance. Series of daily Cone-beam computed tomography (CBCT) images and treatment plan data of a patient with esophageal cancer previously treated using Image-guided radiotherapy (IGRT) were analyzed retrospectively. Daily setup shifts were applied to IMRT plans on a fraction-by-fraction basis using six-degree-of-freedom rigid image registration. The mean interfraction translation displacement was 2.3 ± 1.8, 2.1 ± 0.9, and -1.8 ± 2.6 mm in the LR, AP, and SI directions, respectively. The average interfraction rotation displacement was 2.2 ± 1.2, -0.7 ± 0.8, and -0.7 ± 0.6 degree around the three orthogonal axes. Due to variations, a loss of equivalent uniform dose (EUD) up to 6% for planning target volume (PTV) was noted. Findings confirmed that successful implementation of high precision IMRT required daily image guidance to ensure accurate delivery of sharp gradient dose distributions.

Evaluating the Dosimetric Impact of Interfraction Variations During Image-Guided Radiotherapy Using Six-degree-of-freedom Image Registration and Equivalent Uniform Dose Method

In this paper, the H 2 guaranteed cost control problem of uncertain continuous T-S fuzzy systems is investigated. We approach this problem by considering the multiple Lyapunov function and utilizing the non-PDC controller. Sufficient conditions for ensuring certain H 2 cost as well as asymptotical stability are derived and expressed in terms of LMIs. Unlike existing approaches, the assumption of known upper bounds on the time derivative of membership functions, which is quite unrealistic, is not required anymore in the present one. Numerical examples are also given to demonstrate our approach has lower H 2 guaranteed cost as well as control force in comparison with the existing ones.

H 2 guaranteed cost of uncertain continuous T-S fuzzy systems by multiple Lyapunov function approach

In this study, 14 treatment planning dose parameters for head and neck cancer are adopted as the characteristic functions to establish the statistical analysis of the fuzzy system module for radiation treatment plan classification. By constructing fuzzy rules and fuzzy set membership functions, we aim to improve the classification efficiency and accuracy by the fuzzy systems, and to improve the quality of the treatment plan. Three different fuzzy logic control systems were used for analysis of 100 Pinnacle treatment planning system datasets. The results show that the accuracy may be up to 100%. The fuzzy logic control system we propose may be a useful tool for accurate planning and decision-making.

A fuzzy system for evaluating radiation treatment plans of head and neck cancer

This paper deals with the stabilization problem for discrete-time nonlinear systems that are represented by the Takagi -Sugeno fuzzy model. By the multiple fuzzy Lyapunov function and the three-index algebraic combination technique, a new stabilization condition is developed. The condition is expressed in the form of linear matrix inequalities (LMIs) and proved to be less conservative than existing results in the literature. Finally, a truck-trailer system is given to illustrate the novelty of the proposed approach.

Stabilization of discrete-time nonlinear control systems - Multiple fuzzy Lyapunov function approach

A straightforward approach is presented to realize a completely singular system for in arbitrary polynomial matrix, two special coordinate farms frequently used in the analysis and design of singular systems can be simultaneous obtained.

Chun-Hsiung Fang

Papers

Evaluating the Dosimetric Impact of Interfraction Variations During Image-Guided Radiotherapy Using Six-degree-of-freedom Image Registration and Equivalent Uniform Dose Method

H 2 guaranteed cost of uncertain continuous T-S fuzzy systems by multiple Lyapunov function approach

A fuzzy system for evaluating radiation treatment plans of head and neck cancer

Stabilization of discrete-time nonlinear control systems - Multiple fuzzy Lyapunov function approach

Straightforward approach to completely singular system realization for arbitrary polynomial matrices