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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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Application of BP Neural network model based on genetic in image matching

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Journal of Information and Computational Science 2004年第3期1卷 267-271页

作者： Shi, Zhenghao Feng, Yaning Huang, Shitan Li, Changhe Sch. of Comp. Sci. and Eng. Xi'an Univ. of Technol. Xi'an 710048 China Xi'an Inst. of Microelectronics Xi'an 710054 China

The image matching algorithm is the core of image matching aided navigation systems. Many algorithms have been proposed to improve the accuracy and real-time performance of image matching. Due to its capability of high-speed information processing and uncertainty information processing, Feature point based Artificial Neural Network image matching method has attracted considerable attention in recent years. Yet the result of Feature point based Artificial Neural Network image matching is affected greatly by many factors, such as object occlusions, lighting conditions and noises, especially the ANN algorithm being used, therefore it is important to find a robust feature point based ANN matching algorithm. This paper presents an image registration method based on the BP (Back Propagation) neural networks, where the input data used for registration are the locations of the points extracted from the images with the Directional Wavelet Transform method. To improve the performances of training of ANN for image matching, the genetic algorithm, a well-known global search algorithm, is introduced to BP algorithm to obtain the initial weights and biases. Experimental results showed that the enhanced ANN greatly improved the convergence speed and the matching accuracy for image matching.

关键词： image processing

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POCS supperresolution image reconstruction using wavelet transform

POCS supperresolution image reconstruction using wavelet tra...

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IEEE International Symposium on Intelligent Signal processing and Communication systems (ISPACS)

作者： B. Tian R.J. Sclabassi J.T. Hsu Qiang Liu Lin-Sen Pon Ching-Chung Li Mingui Sun Laboratory for Computational Neuroscience University of Pittsburgh Xi'an Shaanxi China State Key Laboratory of Integrated Services Networks Xidian University Xi'an Shaanxi China Laboratory for Computational Neuroscience Department of Neurological Surgery Biomedical Engineering and Electrical Engineering University of Pittsburgh Xi'an Shaanxi China Laboratory for Computational Neuroscience Electrical Engineering University of Pittsburgh Xi'an Shaanxi China Electrical Engineering University of Pittsburgh Xi'an Shaanxi China

Research interest in multi-frame supperresolution has risen substantially in recent years and it is expected to have wide applications to medicine. This paper presents a modified projection onto convex sets (POCS) superresolution method based on the wavelet transform. Based on the principle of POCS, an iterative procedure is proposed to extract information hidden in a group of low resolution images to update the corresponding high frequency band of the reference image, thus augmenting the individual low-resolution image to a high resolution image. The simulation results show that the new proposed algorithm is effective in constructing high-resolution medical images.

关键词： image reconstruction Wavelet transforms image resolution Spatial resolution Signal resolution Frequency Strontium Biomedical imaging Medical diagnostic imaging Signal processing algorithms

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

作者： Wen-xiang Peng Rong Jia Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China Institute of Water Resources and Hydro-electric Engineering Xi''an University of Technology Xi'an 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.

关键词： Genetic algorithms Algorithm design and analysis Cost function Dynamic programming Linear programming Design optimization image processing Pattern recognition Water resources Resource management

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Updating algorithm for extracting the basis of Karhunen-Loeve transform in nonzero mean data

Updating algorithm for extracting the basis of Karhunen-Loev...

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International Conference on Signal processing Proceedings (ICSP)

作者： Qu Yanyun Zheng Nanning Li Cuihua Yuan Zejian Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China Department of Computer Science Xiamen University Xiamen China

Karhunen-Loeve transform (KLT) is a popular method for dimensional reduction and feature extraction in image analysis, signal processing and automatic control systems and so on. The drawback of the KLT is expensive computation. So the efficient updating algorithms were proposed in signal processing and numerical linear algebra. The updating algorithms make the active learning and recognition possible. But they mainly deal with zero mean data. In this paper, we propose an updating algorithm for KLT for nonzero mean data. And we also show its application in face analysis. The experimental results demonstrate the efficiency of our algorithm.

关键词： Data mining Karhunen-Loeve transforms Signal processing Signal processing algorithms Vectors Robotics and automation Linear algebra image sequence analysis Principal component analysis Face recognition

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A new approach to automatic music video summarization

A new approach to automatic music video summarization

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IEEE International Conference on image processing

作者： xi Shao Changsheng Xa M.S. Kankanhalli Institute for Infocomm Research Singapore School of Computing National University of Singapore Singapore National University of Singapore Singapore SG Sch. of Comput. Nat. Univ. of Singapore Singapore

A new automatic summarization approach for music videos is presented. The proposed method detects and recognizes lyric captions appearing commonly in karaoke music videos and uses the captions to analyze music video structure and identify the most salient music part. The music video summary is created based on the salient part. Experimental results show our proposed method is promising.

关键词： Multiple signal classification Gunshot detection systems Video sequences Frequency Watches Fans Motion pictures Algorithm design and analysis Dynamic programming Heuristic algorithms

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Background clutter and detection algorithm-based Staring IR Seeker Performance Evaluation

Background clutter and detection algorithm-based Staring IR ...

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Photonics Asia 2004;Sensors and Imaging

作者： Hong-hua Chang Jian-qi Zhang xiao-rui Wang Yong Li (School of Technical Physics, xidian University, xi 'an shanxi 710071, People's Republic of China xi 'an institute of applied optics, xi 'an shanxi 710065, People s Republic of China)

Detecting a target out of its surrounding background is a major problem in various infrared seekers. The cluttered scenarios present extreme challenges for the modern IR seekers and are the focus of technology efforts. So, a complete performance evaluation model should include all of the following elements: i) the background ii) the target, iii) the atmosphere, iv) the sensor, and Ⅴ) the image processing algorithms. Since the staring IR seeker systems are emerging as the latest application of the thermal infrared technology, it suffers the most from the lack of complete performance evaluation *** present a robust performance evaluation technique for staring IR seekers based on signal-to-interference ratio (SIR), with the quantitative description of the background clutter and detection algorithms emphasized. The power transfer functions of the optical system, detector and electronic are established to describe energy transmission of the signal and interference (noise and clutter) through the IR seeker, and the targets' radiant intensity statistics as well as the noise's statistical characteristics are also taken into account. In order to quantify the background clutter, we use a clutter measure based on its energy content-power spectral density (PSD). Based on this measure, a SIR is developed to analyze detection performance. Furthermore, the influence of several classical detection algorithms on the SIR is analyzed.

关键词： Staring IRFPA, Background clutter, Signal-to-Interference Ratio, Wavelet, Detection algorithm

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Effect of acquisition system features on algorithm performance

Effect of acquisition system features on algorithm performan...

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Conference on Machine Vision Applications in Industrial Inspection xi

作者： Venkatachalam, V Wasserman, RM Yoshida, H Asano, H Takahama, Y Micro Encoder Inc Kirkland WA 98034 USA

ISBN: (纸本)0819448117

While evaluating the performance of image processing algorithms, the starting point is often the acquired image. However, in practice, several factors, extrinsic to the actual algorithm, affect its performance. These factors depend largely on the features of the acquisition system. This paper focuses on some of the key factors that affect algorithm performance, and attempts to provide some insight into defining "optimal" system features for best performance. The system features studied in depth in the paper are camera type, camera SNR, pixel size, bit-depth and system illumination. We were primarily interested in determining the effect of each of these factors on system performance. Towards this end, we designed an experiment to measure performance on a precision measurement system using several different cameras under varying illumination settings. From the results of the experiment, we observed that the variation in performance was greater for the same algorithm under different test system configurations, than for different algorithms under the same system configuration. Using these results as the basis, we discuss at length the combination of features that contributes to an optimal system configuration for a given purpose. We expect this work to have relevance to researchers in all areas of image processing who want to optimize the performance of their algorithms when ported to actual systems.

关键词： vision systems image acquisition performance SNR quantization bit-depth illumination

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image recognition using a quadratic convergent learning algorithm of synergetic neural network

Image recognition using a quadratic convergent learning algo...

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IEEE International Conference on Robotics, Intelligent systems and Signal processing, RISSP 2003

作者： Sheng, R.Q. Qiao, Hong Chen, Bing Department of Computer Science Shanghai Jiaotong University Shanghai200030 China Department of Computation UMIST M60 1QD United Kingdom Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an710049 China

This paper presents a learning algorithm of synergetic neural network that can be realized by a 2-layered network. A main feature of the new algorithm is that it is of high accuracy and quadratic convergence rate. Further it avoids the error being accumulated. The experiment results show that the algorithm enables the synergetic neural network to recognize images more effectively compared with previous algorithms. © 2003 IEEE.

关键词： Learning algorithms

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Automated image registration in the semiconductor industry: a case study in the direct to digital holography inspection system

Automated image registration in the semiconductor industry: ...

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Conference on Machine Vision Applications in Industrial Inspection xi

作者： Dai, XL Hunt, MA Long Corp Round Rock TX 78681 USA

ISBN: (纸本)0819448117

Automated image registration based on pattern recognition is a critical procedure in many applications of machine vision and is essential for accurate navigation and change detection. In this paper;an overview of the specific applications of image registration in wafer inspection is given, followed by a case study in the application of image registration for direct to digital holography (DDH) wafer inspection. A complete system of novel algorithms for holographic image registration is then presented. In the case of DDH system with complex data flows, the proposed registration system is capable of accepting a variety of data streams as inputs: (1) complex frequency data;(2) complex spatial data;(3) magnitude data extracted from holograms;(4) phase data extracted from holograms;and (5) intensity-only data. This flexibility facilitates the development of faster, more reliable, and more efficient DDH processing systems, which is important in system optimization and production. In particular, the system enables the use of the full complex wavefront, which contains both reflectance and structural topology information, in the registration process. The added information contained in the wavefront can be utilized for increased robustness and computational efficiency. Both the theory and implementation of the proposed registration system are briefly described within the framework of DDH processing for wafer inspection tasks. Several examples of defect detection and wafer alignment are given with estimates of accuracy and robustness.

关键词： image processing

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