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Metric of image quality based on structural similarity

Guangdian Gongcheng/Opto-Electronic Engineering 2007年第11期34卷 108-113页

作者： Zhu, Li Li, Qiao-Liang Zhang, Ting Wang, Guo-You Lab. for Biometric and Medical Image Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

A new evaluation method of image quality based on its construction simulation is proposed to solve the limit of evaluation of perceptual distortion by analyzing the current characteristic of image quality evaluation method. Whole similarity obtained from luminance, contrast and image construction is the objective evaluation standard of image quality. The method fully considers the characteristic of structure information of image and vision of people, starts from the comprehension function of image context, and sets up the structure simulation computing model to evaluate the subjective perception to image quality. By theory deducing and algorithm validation, the evidences for selecting the image compressed algorithm and evaluating image quality are obtained. Reconstructed image after encoding by compression algorithm SPIHT (Set Partitioning in Hierarchical Trees) is compared with the traditional evaluation image based on Peak Signal-to-noise Ratio (PSNR), and experiment shows that the method proposed in the paper is a more effective evaluating method for image quality.

关键词： Distortion sensitivity image quality evaluation Structural similarity

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Propagation of uncertainty in landmark based self-localization of autonomous mobile robots

Propagation of uncertainty in landmark based self-localizati...

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10th IAPR Conference on Machine Vision Applications, MVA 2007

作者： Bais, Abdul Sablatnig, Robert Khawaja, Yahya M. Novak, Gregor Institute of Computer Technology Vienna University of Technology Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation ViennaUniversity of Technology Vienna Austria Department of Electrical Engineering NWFP University of Engineering and Technology Peshawar Pakistan

ISBN: (纸本)9784901122078

This paper presents uncertainty propagation in landmark based position estimation methods. Analysis of two methods has been carried out where robot position is estimated by detecting one or two globally distinct features using a pivoted stereo vision system. We make a basic assumption about error in estimating point features in camera images and propagate it into robot position estimate using first order approximation of non-linear functions. Simulation results illustrate the performance of the method.

关键词： Stereo image processing

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Electroluminescence Gray Scale Display Driving Method and Circuit

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Semiconductor Photonics and Technology 2007年第3期13卷 225-229页

作者： KANG Hao LI Rong-yu YANG Xin Department of Electronic and Engineering Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 CHN

The increasing use of color terminals for personal computers has raised a demand for video graphic adapter(VGA)-format panel displays. Since only monochrome(ZnS∶Mn) electroluminescence(EL) displays of suitable size and speed are available, lack of colors has to be replaced by grayscale in the first place. There are two basic driving methods to achieve grayscale in thin-film EL displays: pulse amplitude modulation(PAM) method and pulse width modulation(PWM) method. But there are serious disadvantages of the two traditional methods. For the former method, the high voltage PAM ICs are too expensive to produce the grayscale EL display in bulks and the driver integrated circuit(IC) is complex. Though the PWM method has good grayscale display quality, the hardware implementation is too complex. A new driving method with which the width and the amplitude of the pulse can be modulated and simultaneously the challenge can be solved efficaciously is presented.

关键词： electroluminescence（EL） display gray scale representation PAM＆PWM method PWM generator circuit

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Using steepest descent method to refine the node positions in wireless sensor networks

Using steepest descent method to refine the node positions i...

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2007 IET Conference on Wireless, Mobile and Sensor Networks (CCWMSN07)

作者： Q.Q. Shi H. Huo T. Fang R.D. Li Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Shanghai Jiaotong University Shanghai China

Refinement is a necessary and effective step in some node localization schemes of wireless sensor networks (WSN). Suitable refinement procedure can improve the node localization accuracy and raise the robustness of the localization algorithm. However, most existing refinement algorithms are costly duo to complex computation and frequent communication, and may induce serious coverage problem duo to nonconvergent iterations. In view of above facts, Steepest descent method is proposed to be used as the refinement algorithm in this paper, and corresponding simulation experiments are done to testify its feasibility and validity. The results show that steepest descent method can optimize the node positions to a fairish accuracy extent, and compared with existing refinement methods, it outperforms in communication cost, computation cost, and coverage rate.

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Application of "human-in-the-loop" control to a biped walking-chair robot

Application of "human-in-the-loop" control to a biped walkin...

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2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007

作者： Jiaoyan, Tang Qunfei, Zhao Jie, Huang Mechanical Engineering School University of Shanghai Jiao Tong Shanghai 200240 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China College of Computer Science and Engineering University of Aizu Aizu Wakamatsu 965-8580 Japan

ISBN: (纸本)1424409918

This paper presents the research on stability for biped Walking-Chair robot with human-in-the-loop. The inherent properties of the biped system which is developed for the disable people to replace traditional wheelchairs are analyzed. Control of the robot for the gait and navigation is introduced. Posture stability computation method based on ZMP (Zero Moment Point) theory is discussed. Some suggestions about the future research are also presented. © 2007 IEEE.

关键词： Robots

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Robot navigation and sound based position identification

Robot navigation and sound based position identification

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IEEE International Conference on Systems, Man and Cybernetics

作者： Huakang Li Satoshi Ishikawa Qunfei Zhao Michiko Ebana Hiroyuki Yamamoto Jie Huang School of computer science and engineering University of Aizu Japan Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

In this paper, we proposed a robot self position identification method by active sound localization. This method can be used for autonomous security robots working in room environments. A system using a AIBO robot equipped with two microphones and wireless network is constructed and is used for position identification experiments. Arrival time differences to the microphones of robot are used as localization cues. To overcome the ambiguity of front-back confusion, a three-head position measurement method was proposed. The robot position can be identified by the intersection of circles restricted by the azimuth differences to different speaker pairs. By localizing three or four speakers as sound beacons positioned on known locations, the robot can identify its self position with an average error of about 7 cm in a 2.5times3.0 m 2 working space. A robot navigation experiment was conducted to demonstrate the effectiveness of the position identification system.

关键词： Navigation Robot sensing systems Microphones Loudspeakers Humans Mobile robots Azimuth Humanoid robots Orbital robotics Auditory system

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Sparse MRF appearance models for fast anatomical structure localisation

Sparse MRF appearance models for fast anatomical structure l...

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2007 18th British Machine Vision Conference, BMVC 2007

作者： Donner, René Mičušsík, Branislav Langs, Georg Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria GALEN Group Laboratoire de Mathématiques Appliquées Aux Systèmes Ecole Centrale de Paris France

ISBN: (纸本)1901725340

image segmentation methods like active shape models, active appearance models or snakes require an initialisation that guarantees a considerable overlap with the object to be segmented. In this paper we present an approach that localises anatomical structures in a global manner by means of Markov Random Fields (MRF). It does not need initialisation, but finds the most plausible match of the query structure in the image. It provides for precise, reliable and fast detection of the structure and can serve as initialisation for more detailed segmentation steps. Sparse MRF Appearance Models (SAMs) encode a priori information about the geometric configurations of interest points, local features at these points and local features along the edges of adjacent points. This information is used to formulate a Markov Random Field and the mapping of the modeled object (e.g. a sequence of vertebrae) to the query image interest points is performed by the MAX-SUM algorithm. The local image information is captured by novel symmetry-based interest points and local descriptors derived from Gradient Vector Flow. Experimental results are reported for two data-sets showing the applicability to complex medical data.

关键词： image segmentation

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A Modified Numerical Integration Method for Deformable Object Animation

A Modified Numerical Integration Method for Deformable Objec...

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Asia Simulation Conference 2007, AsiaSim 2007

作者： Hu, Xinrong Wei, Lan Li, Dehua Dept. of Computer Science and Technology WuHan University of Science and Engineering WuHan 430074 China Institute for Pattern Recognition and Artificial Intelligence State Education Commission Laboratory for Image Processing and Intelligence Control HuaZhong Univ. of Science and Technology WuHan 430074 China

ISBN: (纸本)9783540775997

A satisfied deformable object simulation should be general, accurate, efficient and stable. Explicit, implicit and semi-implicit numerical integration methods have contributed to large performance enhancements in the field of deformable simulation. Cloth is the most representative deformable object. In this paper, we propose an improved embedded Runge-Kutta integration method to solve the deformable simulation that based on classical spring-mass model. Traditional embedded Runge-Kutta methods generally solve ordinary differential equations of deformable object simulation. Most of them tend to concentrate on the efficiency of the simulation process, and not the fidelity of the simulation result. We investigate and determine the extent to which the overall quality must be compromised in order for the stable conditions to be satisfied. The improved Runge-Kutta method proposed in our paper incorporates the fixed time step and adaptive time step in solving cloth motion equations to achieve a controllable error evaluation. Compared with the other Runge-Kutta methods, the proposed method has some advantages for cloth simulation: controllable error evaluation without extra computations, excellent efficiency, good stability and satisfied precision. Experiment demonstrates that this method results in simulation efficiency improvements and is considerable practicable. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Animation

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ML Nonlinear Smoothing for image Segmentation and its Relationship to the Mean Shift

ML Nonlinear Smoothing for Image Segmentation and its Relati...

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IEEE International Conference on image processing

作者： Andy Backhouse Irene Y. H. Gu Tiesheng Wang Department of Signals and Systems Chalmers University of Technology Sweden Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

This paper addresses the issues of nonlinear edge-preserving image smoothing and segmentation. A ML-based approach is proposed which uses an iterative algorithm to solve the problem. First, assumptions about segments are made by describing the joint probability distribution of pixel positions and colours within segments. Based on these assumptions, an optimal smoothing algorithm is derived under the ML condition. By studying the derived algorithm, we show that the solution is related to a two-stage mean shift which is separated in space and range. This novel ML-based approach takes a new kernel function. Experiments have been conducted on a range of images to smooth and segment them. Visual results and evaluations with 2 objective criteria have shown that the proposed method has led to improved results which suffer from less over-segmentation than the standard mean-shift.

关键词： Smoothing methods image segmentation Maximum likelihood estimation Iterative algorithms Filters Kernel Stochastic processes Robustness Signal processing image processing

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Object Tracking using Incremental 2D-PCA Learning and ML Estimation

Object Tracking using Incremental 2D-PCA Learning and ML Est...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Tiesheng Wang Irene Y.H. Gu Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai JiaoTong University China Department of Signals and Systems Chalmers University of Technology Sweden

Video surveillance has drawn increasing interests in recent years. This paper addresses the issue of moving object tracking from videos. A two-step processing procedure is proposed: an incremental 2DPCA (two-dimensional principal component analysis)-based method for characterizing objects given the tracked regions, and a ML (maximum likelihood) blob-tracking process given the object characterization and the previous blob sequence. The proposed incremental 2DPCA updates the row- and column-projected covariance matrices recursively, and is computationally more efficient for online learning of dynamic objects. The proposed ML blob-tracking takes into account both the shape information and object characteristics. Tests and evaluations were performed on indoor and outdoor image sequences containing a range of single moving object in dynamic backgrounds, which have shown good tracking results. Comparisons with the method using the conventional PCA were also made.

关键词： Maximum likelihood estimation Principal component analysis Covariance matrix Target tracking Shape Video surveillance image processing pattern recognition Signal processing Recursive estimation

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