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20th ISPRS Congress on Technical Commission VII

作者： He, Binbin Fang, Tao Guo, Dazhi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University No.1954 Huashan Road Shanghai200030 China Department of Environment and Spatial Informatics China University of Mining and Technology Xuzhou JiangSu221008 China

Although uncertainties exist in spatial knowledge discovery, they have not been paid much attention to. In the past years, the most researches of spatial knowledge discovery focused on the methods of data mining and its algorithms. In this paper, uncertainty and its propagation of spatial data are discussed and analysed firstly. Then, uncertainties at various stages of spatial knowledge discovery are briefly analysed, including data selection, data preprocessing, data mining, knowledge representation and uncertain reasoning. Thirdly, a method of spatial knowledge discovery in conjunction with uncertain reasoning by means of fuzzy evidence theory is proposed. Herein, the framework for uncertainty handling in spatial knowledge discovery is constructed, and the fundamental issues include soft discretization of spatial data, fuzzy transformation between quantitative data and qualitative concept, reasoning under uncertainty and uncertain knowledge representation. © 2004 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Data mining

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Improved genetic algorithms for optimal design of drainage systems

Improved genetic algorithms for optimal design of drainage s...

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8th International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Peng, Wen-Xiang Jia, Rong Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University 1954 Huashan Road Shanghai 200030 China Institute of Water Resources and Hydro-Electric Engineering Xi'an University of Technology 5 South Jinhua Road Xi'an 710048 China

ISBN: (纸本)0780386531

The optimization of existing sewer systems or making new systems is and will remain one of the key issues in drainage management in our society. The problem consists of minimization of a nonlinear cost function subjected to nonlinear constraints. To overcome the difficulties of the optimization of drainage systems, in this paper, an Elitist Adaptive Genetic Algorithm (EAGA) for pipe optimization has been developed, by integrating Elitist Genetic Algorithm (EGA) with Adaptive Genetic Algorithm (AGA). We compare the performance of the EAGA with that of EGA and AGA in optimizing sewer systems. The EAGA converges to the global optimum in far fewer generations than the EGA and AGA. We believe that the EAGA is the first step in realizing a class of self-organizing Genetic Algorithms (GAs) capable of adapting themselves in locating the global optimum in drainage systems. © 2004 IEEE.

关键词： Drainage

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Edge detection in range images of piled box-like objects

Edge detection in range images of piled box-like objects

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International Conference on pattern recognition

作者： D. Katsoulas A. Werber Institute of Pattern Recognition and Image Processing Albert Ludwigs University of Freiburg Freiburg im Breisgau Germany

We present a framework for edge detection in range images acquired by a time of flight laser sensor. Our edge detection approach is inspired by Jiang, X and Bunke, H (Feb., 1999), in the context of which edge detection via scan line approximation with geometric parametric models is performed. The main drawback of this edge detector, namely the scan line over-segmentation problem is addressed by the introduction of a simple merging step. In addition, we incorporate a method for detection of the noisy data points created by the effect of laser beam splitting between surfaces of different ranges. Finally, a procedure for fine localization of the edge points is introduced. Experimental results on a variety of target object configurations demonstrate that our edge detection framework exhibits increased robustness and accuracy with regard to Jiang, X and Bunke, H (Feb., 1999). These characteristics in combination with the computational efficiency of our approach, allows for its usage as a component of a real time system for automatic unloading of piled box-like objects.

关键词： image edge detection Laser modes image sensors Parametric statistics Detectors Merging Optical beam splitting Surface emitting lasers Robustness Computational efficiency

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Initial estimates for robotic hand-eye calibration

Initial estimates for robotic hand-eye calibration

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International Workshop on Robot Sensing (ROSE)

作者： Hong-Jian Liu Fan-Huai Shi Yun-Cai Liu Yi Luo Institute of Image Processing & Pattern Recognition Shanghai Jiao Tong University Shanghai People's Republic of China

ISBN: (纸本)078038296X

An initial estimates method for calibration of a robotic hand-eye relationship is presented in the paper. Classical methods mainly concentrate on solving the basic equation AX=XB, where X is the unknown sensor position relative to the robot hand, A is the robot motion, B is the camera motion. In optimizing process of solving the equation, initial values are needed. Unsuitable initial values often lead to a big error. The proposed method has a large advantage on getting a fine initial value, which can avoid errors introduced by experience effective. Real experiments have been used to test the proposed method and good results have been obtained.

关键词： Calibration Robot kinematics Robot vision systems Cameras Equations Robot sensing systems Robotics and automation Iterative algorithms pattern recognition Robot motion

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Kernel-bandwidth adaptation for tracking object changing in size

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1st International Conference on image Analysis and recognition, ICIAR 2004

作者： Peng, Ning-Song Yang, Jie Chen, Jia-Xin Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University P.O. Box 104 1954 Huashan Road Shanghai200030 China Institute of Electronic and Information Henan University of Science and Technology Luoyang471039 China

ISBN: (纸本)3540232400

In the case of tracking object changing in size, traditional mean-shift based algorithm always leads to poor localization owing to its unchanged kernel-bandwidth. To overcome this limitation, a novel kernel-bandwidth adaptation method is proposed where object affine model is employed to describe scaling problem. With the registration of object centroid in consecutive frames by backward tracking, scaling magnitude in the affine model can be estimated with more accuracy. Therefore, kernel-bandwidth is updated with respect to the scaling magnitude so as to keep up with variety of object size. We have applied the proposed method to track vehicles changing in size with encouraging results. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Bandwidth

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On 3D mosaicing of rotationally symmetric ceramic fragments

On 3D mosaicing of rotationally symmetric ceramic fragments

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International Conference on pattern recognition

作者： M. Kampel R. Sablatnig Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

A major obstacle to the wider use of 3D object reconstruction and modeling is the extent of manual intervention needed. Such interventions are currently massive and exist throughout every phase of a 3D reconstruction project: collection of images, image management, establishment of sensor position and image orientation, extracting the geometric detail describing an object, merging geometric, texture and semantic data. This work aims to develop a solution for automated documentation of archaeological pottery, which also leads to a more complete 3D model out of multiple fragments. Generally the 3D reconstruction of arbitrary objects from their fragments can be regarded as a 3D puzzle. In order to solve it we identified the following main tasks: 3D data acquisition, orientation of the object, classification of the object and reconstruction. We demonstrate the method and give results on synthetic and real data.

关键词： Ceramics image reconstruction pattern recognition Assembly Surface cracks Surface reconstruction Automation image processing Manuals Project management

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A fast VLSI architecture for two-dimensional discrete wavelet transform based on lifting scheme

A fast VLSI architecture for two-dimensional discrete wavele...

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2004 7th International Conference on Solid-State and Integrated Circuits Technology Proceedings, ICSICT 2004

作者： Xiong, Chengyi Tian, Jinwen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence Key Laboratory of Eduaction Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China College of Electronic Information Engineering South-Center University for Nationalities Wuhan 430074 China

This paper proposes a novel fast architecture for two-dimensional discrete wavelet transform by using lifting scheme. The parallel and embedded decimation techniques are employed to optimize the architecture, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. The architecture is designed to generate two outputs at one working clock cycle, with every two subbands coefficients alternately. The total time of computing J levels of decomposition for N×N image is approximately 2N2(I-4 J)/3 clock cycles. In comparison with the other devices reported in previous literature, the design has many advantages including lower hardware complexity and area and power efficient. The design is also fast, regular and simple, as well as well suited for VLSI implementation. © 2004 IEEE.

关键词： VLSI circuits

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Mean-shift blob tracking with kernel-color distribution estimate and adaptive model update criterion

Mean-shift blob tracking with kernel-color distribution esti...

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2nd International Workshop on Statistical Methods in Video processing, SMVP 2004 held in conjuction with 8th European Conference on Computer Vision, ECCV 2004

作者： Peng, Ning-Song Yang, Jie Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University P.O. Box 104 No.1954 Huashan Road Shanghai200030 China Institute of Electronic and Information Henan University of Science and Technology Luoyang471039 China

ISBN: (纸本)9783540302124

We propose an adaptive model update mechanism for mean-shift blob tracking. It is novel for us to use self-tuning Kalman filters for estimating object kernel-color distribution, i.e. kernel-histogram. Filtering residuals are employed for hypothesis testing in order to obtain a robust criterion for model update. Therefore, tracker has the ability to keep up with the changes of object appearance as well as the changes in scale. Moreover, over-update is avoided in the cases of severe occlusion and dramatic appearance changes. Various tracking sequences demonstrate the superior behavior of our tracker which runs in real-time with non-parameter initialization and is robust to appearance changes. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Kalman filters

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Blurred image recognition based on complex moment invariants

Blurred image recognition based on complex moment invariants

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IEEE International Conference on image processing

作者： Zhang Tianxu Liu Jin Institute for Pattern Recognition and Artificial Intelligence Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

ISBN: (纸本)0780385543

An important class of radiometric degradations we are faced with often in practice is image blurring. Special attention is paid to the recognition of the blurred image by moment invariant approach. Some important rules of complex moments for the blurred image are presented. Based on these rules, a useful subset of moment invariants is introduced, that are not affected by the blur, rotation, scale, and translation of the images. The experiments have shown that these invariants can be successfully used in recognition of the blurred image.

关键词： image recognition Layout Convolution Radiometry Character recognition Target recognition Computer vision Biomedical imaging Degradation Cameras

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A new noise erosion operator for anisotropic diffusion

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激光与光电子学进展 2004年第5期2卷 268-270页

作者：蔡超丁名跃周成平张天序 Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applied to estimate a new diffusion coefficient. Experimental results demonstrate that anisotropic diffusion based on this new erosion operator can efficiently reduce noise and sharpen object boundaries.

关键词： partial differential equation diffusion coefficient anisotropic diffusion

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