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An Image Matching Evolutionary Algorithm Based on Hu Invariant Moments

An Image Matching Evolutionary Algorithm Based on Hu Invaria...

2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

作者： Ruliang Zhang Lin Wang Key Laboratory of Pattern Recognition and Intelligent Control Guizhou University for NationalitiesGuiyang China

ISBN: (纸本)9781612848792

This paper presents an image matching evolutionary algorithm (called IMEA algorithm) based on Hu invariant moments. First, the population is initialized. A group of searched subgraphs is constructed. Second, the fitness function based on Hu invariant moments is designed. The seven Hu invariant moments of the template image and the searched subgraph are calculated. The Euclidean distance of Hu invariant moments is used to measure similarity between the template image and the searched subgraph. The template image and the searched subgraph are matched if these Euclidean distances are less than the set threshold. Finally, a new searched subgraph is constructed by means of a new evolutionary strategy. The new searched subgraph replaces the searched subgraph whose value of the fitness function is maximum. Experimental results demonstrate the great robustness and efficiency of the IMEA algorithm.

关键词： Hu invariant moments evolutionary algorithm euclidean distance image matching

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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电子学报(英文版) 2010年第3期19卷 451-456页

作者： LI Bo LIU Wenju DOU Lihua School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词：高斯混合模型图像分割无监督学习应用概率密度函数椭球等高分布模型估计高斯密度

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License Plate Character recognition Based on Gaussian-Hermite Moments

License Plate Character Recognition Based on Gaussian-Hermit...

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International Workshop on Education Technology and Computer Science, ETCS

作者： Xiaojuan Ma Renlong Pan Lin Wang Guizhou Key Laboratory of Pattern Recognition & Intelligent Control Guizhou University for Nationalities Guiyang China

ISBN: (纸本)9781424463886;9780769539874

Character recognition plays an important role in the automatic license plate recognition (ALPR) system. In this paper, we propose a new method to recognize the license plates characters by using 2D Gaussian-Hermite moments (GHMs) of different orders with 231 GHMs features as the input vector of BP neural network. The system worked under variable illumination, variable size of plate and dynamic backgrounds. The experimental results demonstrate robust and efficient of our method.

关键词： Licenses Character recognition Gaussian processes Neural networks pattern recognition Image segmentation intelligent transportation systems Robustness Image recognition pattern analysis

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Learning GMM Using Elliptically Contoured Distributions

Learning GMM Using Elliptically Contoured Distributions

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International Conference on pattern recognition

作者： Bo Li Wenju Liu Lihua Dou Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China Beijing Institute of Technology Beijing Beijing CN

Model order selection and parameter estimation for Gaussian mixture model (GMM) are important issues for clustering analysis and density estimation. Most methods for model selection usually add a penalty term in the objective function that can penalize the models and choose an optimal one from a set of candidate models. This paper presents a simple and novel approach to determine the number of components and simultaneously estimate the parameters for GMM. By introducing the degenerating model, the proposed approach overcomes the drawback of likelihood estimate that is a non-decreasing function and can not be used to select the number of components. The degenerating model is a more general form of mixture component density and it can degenerate into the component density or a crater-like density when its parameter K varies from 1 to a bigger value. The likelihood of the crater-like density evaluated for the training data approximates to zero. This characteristic of the degenerating model forms the foundation of the proposed approach. The experimental results show robust and evident performance improvement of the approach.

关键词： Hidden Markov models Training Programming Gaussian distribution Density functional theory Computational modeling Estimation

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N-order difference heuristic model of fuzzy time series forecasting

N-order difference heuristic model of fuzzy time series fore...

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IEEE International Conference on intelligent Computing and intelligent systems (ICIS)

作者： Kai Chi Wen-Gang Che Pattern Recognition and Intelligent System School of Information Engineering and Automation Kunming University of Science and Technology China Key Laboratory of Computer Technology and Application of Yunnan Province Kunming University of Science and Technology China

Fuzzy time series forecasting model is an effective method to solve the nonlinear problems forecasting. However, most published fuzzy time series based models did not count the change trend implicit in historical datum. In this paper, authors proposed a novel method which applied heuristic information to the fuzzy time series model based on Fibonacci sequence. As an example, the USD/JPY exchange rate is tested in this model. The results show that this method not only improves the forecasting accuracy, but decreases the computational complexity.

关键词： Predictive models Technology forecasting Economic forecasting Uncertainty Fuzzy systems pattern recognition intelligent systems Automation Channel hot electron injection Laboratories

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An Improved Adaptive Exponential Smoothing Model for Short-term Travel Time Forecasting of Urban Arterial Street

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自动化学报 2008年第11期34卷 1404-1409页

作者： LI Zhi-Peng YU Hong LIU Yun-Cai LIU Fu-Qiang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 P.R. China Intelligent Transportation System Department Shanghai Electrical Apparatus Research Institute Shanghai 200063 P. R. China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 P. R. China

旅行时间的短期的预报为聪明的交通系统的成功是必要的。在这份报纸，我们考察预报模型的短期的交通的 state-of-art 并且构画出他们每个模型的基本想法，相关工作，优点和劣势。一改进适应指数的变光滑(IAES ) 模型也被建议克服以前的... 详细信息

旅行时间的短期的预报为聪明的交通系统的成功是必要的。在这份报纸，我们考察预报模型的短期的交通的 state-of-art 并且构画出他们每个模型的基本想法，相关工作，优点和劣势。一改进适应指数的变光滑(IAES ) 模型也被建议克服以前的适应指数的变光滑模型的缺点。然后，比较实验在状况和反常交通调节评估在牌照匹配获得的直接旅行时间数据(每分钟行数) 上预报模型的四个主要分支的性能的正常交通下面被执行。实验的结果证明每个模型似乎有它的自己的力量和软弱。IASE 的预报表演比在更突然预报地平线(预报的和二步) 的另外的模型优异， IASE 能够处理各种交通条件。

关键词：自适应指数平滑模型短期旅行时间预测预测方法信息处理技术城市街道设计方案

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An Improved Adaptive Exponential Smoothing Model for Short-term Travel Time Forecasting of Urban Arterial Street

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Acta Automatica Sinica 2008年第11期34卷 1404-1409页

作者： Zhi-Peng LI Hong YU Yun-Cai LIU Fu-Qiang LIU Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 P. R. China Intelligent Transportation System Department Shanghai Electrical Apparatus Research Institute Shanghai 200063 P. R. China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 P. R. China

Short-term forecasting of travel time is essential for the success of intelligent transportation system. In this paper, we review the state-of-art of short-term traffic forecasting models and outline their basic ideas, related works, advantages and disadvantages of each model. An improved adaptive exponential smoothing (IAES) model is also proposed to overcome the drawbacks of the previous adaptive exponential smoothing model. Then, comparing experiments are carried out under normal traffic condition and abnormal traffic condition to evaluate the performance of four main branches of forecasting models on direct travel time data obtained by license plate matching (LPM). The results of experiments show each model seems to have its own strength and weakness. The forecasting performance of IASE is superior to other models in shorter forecasting horizon (one and two step forecasting) and the IASE is capable of dealing with all kind of traffic conditions.

关键词： Travel time short-term forecasting license plate matching (LPM) exponential smoothing

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Study of software fault tolerance system evaluation strategy

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Wuhan Daxue Xuebao (Xinxi Kexue Ban)/ Geomatics and Information Science of Wuhan University 2008年第10期33卷 1018-1021页

作者： Liu, Xin Yin, Qian Guo, Ping Lab. of Pattern Recognition and Intelligent System Beijing Normal University 19 Xinjiekou Beijing 100875 China State Key Laboratory of Computer Science Institute of Software CAS 4 Zhongguancun Beijing 100080 China

Software fault tolerance technique is used to ensure high reliability. In order to evaluate the quality of fault-tolerant systems, expected execution time and cost must be considered. A new evaluation strategy is proposed to evaluate, evaluating the system with three groups of quality factors, which is the capability, the time and the cost. By using them, the system's integrative quality factor can be calculated. When applying this strategy, we compare the quality of software systems which is consist of different fault-tolerant components. The results can be used to improve fault-tolerant system. To achieve the required optimal result, several optimization schemes are given to meet different project demands.

关键词： Quality control

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Extraction of tree height from large viewing angle aerial images

Extraction of tree height from large viewing angle aerial im...

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International Conference on Space Information Technology

作者： Li, Chaoyang Yan, Guangjian Liu, Qiang Xiao, Zhiqiang Wang, Jingdi Laboratory of Pattern Recognition and Intelligent System School of Information Engineering Beijing University of Posts and Telecommunications 86-10-58809966 China State Key Laboratory of Remote Sensing Science Beijing Normal University Institute of Remote Sensing Applications Research Center for Remote Sensing School of Geography Beijing Normal University

ISBN: (纸本)0819460079

Due to the complexity and non-regularity of tree shapes, traditional digital photogrammetry using stereo matching method is difficult to obtain the accurate tree height, This fact therefore limits the application of the aerial digital photogrammetry technology in the power line survey. This paper presents a method of tree height extraction from large viewing aerial image using the knowledge of segmented tree crown. This method is based on a rough digital surface model (DSM) of tree crowns and the exterior orientation of the image. The basic steps of this method is that the DSM is first used to find the region of interest in the image based on the exterior orientation, and then the edges of the distinct trees or branches are extracted using image segmentation technology. An algorithm that uses both the rough DSM height information and exterior orientation data to calculate the accurate heights of the segmented trees or branches is presented. The algorithm assumes that most of the trees are upright, and the projection in the large viewing angle images of the crown and branches can therefore be used to calculate their heights relative to the averaged DSM height. Hence, the accurate height of the trees around the rough DSM can be refined. Some experimental results are given with the image captured from multi-angular imaging system mounted on a helicopter in which a Position and Orientation system (POS) is onboard to record the exterior element of the cameras. The experimental results demonstrated that this algorithm can largely improve the accuracy of tree height extraction. The application in power line monitoring system is promising.

关键词： Image processing

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