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Geometric Invariant Shape Classification Using Hidden Markov Model

Geometric Invariant Shape Classification Using Hidden Markov...

引用

Proceedings of the Digital Image computing: Technqiues and Applications (DICTA)

作者： Chi-Man Pun Cong Lin Department of Computer and Information Science University of Macau Macao China

In this paper we propose a novel approach for geometric shape classification by using shape simplification and discrete Hidden Markov Model (HMM). The HMM is constructed using the landmark points obtained from the shape simplification for each shape image in the dataset. Some useful strategies have been employed for the constructed HMM for geometric shape classification. Experimental results based on the common MPEG7 CE shapes database shows that our proposed method can achieve very good accuracy in different kinds of shapes.

关键词： Shape Hidden Markov models pattern recognition Transforms Turning Markov processes Databases

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recognition of unideal iris images using region-based active contour model and game theory

Recognition of unideal iris images using region-based active...

引用

IEEE international conference on Image Processing

作者： Kaushik Roy Prabir Bhattacharya Ching Y. Suen Jane You Centre of Pattern Recognition and Machine Intelligence Concordia University Montreal Canada Department of Computer Science University of Cincinnati OH USA Department of Computing Science Hong Kong Polytechnic University Hong Kong China

We process the unideal iris images that are acquired in an unconstrained situation and are affected severely by gaze deviations, eyelid and eyelash occlusions, non uniform intensities, motion blurs, reflections, etc. The proposed unideal iris recognition algorithm has two novelties as compared to the previous works; firstly, we propose to deploy a region-based active contour model to segment an unideal iris image with intensity inhomogeneity; Secondly, an iterative algorithm, called the Modified Contribution- Selection Algorithm (MCSA), is used in the context of coalitional game theory to select a subset of informative features without compromising the recognition rate. The verification performance of the proposed scheme is validated using the UBIRIS Version 1, the ICE 2005, and the WVU Unideal datasets.

关键词： Iris recognition Active contours Iris Game theory Image segmentation Level set Ice

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Corner Detection Based on Normal Vector of Boundary Fitting Line

Corner Detection Based on Normal Vector of Boundary Fitting ...

引用

international conference on Genetic and Evolutionary computing (ICGEC)

作者： Zhenyu Meng Jeng-Shyang Pan Kuo-Kun Tseng Chih-Yu Hsu IIIRC Center Department of Computer Science Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Department of Information and Communication Engineering Chaoyang University of Technology Taichung Taiwan

This paper shows a novel and low complexity approach for corner detection which is based on a normal vector of boundary fitting line. It avoids wrong detection of superfluous corners on no-corner arcs. Our proposed method is superior to Sun's k-cosine corner detection in detection time and has a better performance in localization. Our experiment results confirmed that the proposed approach of corner detection has reached our goal. It is free from rotation and able to locate the corner correctly. In addition, it also performs well for scaling images with the adjustable thresholds.

关键词： Detectors Fitting Robustness Noise Complexity theory pattern recognition Image edge detection

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The Identification Research of Airplane Target Based on BP Neural Network

The Identification Research of Airplane Target Based on BP N...

引用

2010 IEEE international conference on Intelligent computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

作者： Guang Yang Bai Zhang Jianfeng Zhang Xiaojuan Wang Zhenyu Pang Hang Li Xianghua Yang Special Profession Department Aviation University of Air Force.Changchun JiLin CHINA 130022 North Northeast Institute of Geography and Agricultural Ecology Chinese Academy of Sciences (CAS) Changch Aviation University of Air Force Changchun JiLin CHINA 130022 Aviation University of Air Force Changchun JiLinCHINA 130022 Foshan Polytechnic College Foshan GuangDong CHINA 528237

The airplane goal's automatic identification is a research hot spot which realizing the target automatic recognition of the remote sensing image. The BP neural network is a multi-layered network which using the non-linear differentiablc function to carry on the weight training. It has contained the most essence part in the neural network theory;the BP neural network has obtained the widespread application in the domains of function approach, pattern Identification, information class and data compression because of its simple structure. Identified and researched the type of airplane based on the artificial neural networks method using the MATLAB software. The result indicated: the accuracy of airplane target recognition may achieve 72.1％ based on the BP neural network and it can meet the needs.

关键词： BP Neural Network Airplane target pattern Identification Network training

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Human activity recognition applying computational intelligence techniques for fusing information related to WiFi positioning and body posture

Human activity recognition applying computational intelligen...

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： A. Alvarez-Alvarez J. M. Alonso G. Trivino N. Hernández F. Herranz A. Llamazares M. Ocaña European Centre for Soft Computing (ECSC) Mieres Asturias Spain Department of Electronics University of Alcalá (UAH) Madrid Spain Department of Electronics University of Alcalá Madrid Spain

This work presents a general framework for people indoor activity recognition. Firstly, a Wireless Fidelity (WiFi) localization system implemented as a Fuzzy Rule-based Classifier (FRBC) is used to obtain an approximate position at the level of discrete zones (office, corridor, meeting room, etc). Secondly, a Fuzzy Finite State Machine (FFSM) is used for human body posture recognition (seated, standing upright or walking). Finally, another FFSM combines both WiFi localization and posture recognition to obtain a robust, reliable, and easily understandable activity recognition system (working in the desk room, crossing the corridor, having a meeting, etc). Each user carries with a personal digital agenda (PDA) or smart-phone equipped with a WiFi interface for localization task and accelerometers for posture recognition. Our approach does not require adding new hardware to the experimental environment. It relies on the WiFi access points (APs) widely available in most public and private buildings. We include a practical experimentation where good results were achieved.

关键词： IEEE 802.11 Standards Pragmatics Input variables Humans Sensors Accelerometers Buildings

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3D FACE recognition BASED ON EVOLUTION OF ISO-GEODESIC DISTANCE CURVES

3D FACE RECOGNITION BASED ON EVOLUTION OF ISO-GEODESIC DISTA...

引用

IEEE international conference on Acoustics, Speech, and Signal Processing

作者： Shun Miao Hamid Krim North Carolina State University Electrical and Computer Engineering Dept. Raleigh NC 27606 USA

ISBN: (纸本)9781424442959

This paper presents a novel 3D face recognition method by means of the evolution of iso-geodesic distance curves. Specifically, the proposed method compares two neighboring iso-geodesic distance curves, and formalizes the evolution between them as a one-dimensional function, named evolution angle function, which is Euclidean invariant. The novelty of this paper consists in formalizing 3D face by an evolution angle functions, and in computing the distance between two faces by that of two functions. Experiments on Face recognition Grand Challenge (FRGC) ver2.0 shows that our approach works very well on both neutral faces and non-neutral faces. By introducing a weight function, we also show a very promising result on non-neutral face database.

关键词： Face recognition Geometric modeling Image registration pattern classification

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An algorithm for vague pattern recognition

An algorithm for vague pattern recognition

引用

2010 international conference on Intelligent computing and Cognitive Informatics (ICICCI 2010)

作者： Chengyi Zhang School of Mathematics and Statistics Hainan Normal University Haikou,ChinaLeng Wang School of Mathematics and Statistics Hainan Normal University Haikou,ChinaHongxu Wang Department of Electronic information engineering Qiongzhou University Sanya,China

The transforming formula definition from the single valued data to vague valued data was presented,and two transfo-rming formulas from the single valued data to vague valued data were presented,and a similarity measures between vague sets was presented,and an algorithm for vague pattern recognition was *** has been further expounded through an application living example for battlefield targets identification that this algorithm is practicable.

关键词： vague pattern recognition algorithm vague value data similarity measures battlefield targets identification

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Sound as an Aid in Understanding Low-Level Program Architecture

Sound as an Aid in Understanding Low-Level Program Architect...

引用

IEEE Workshop on Program Comprehension

作者： Lewis Berman School of Engineering and Computing Sciences University of Durham Durham UK

A tool and associated sound mapping have been developed for exploring and understanding the static structure of Java programs' packages, classes, interfaces, and methods. The tool supplements visual use of the Eclipse IDE. A sound mapping provides information regarding the identification of, characteristics of, and relationships among the architectural entities.

关键词： Packaging Java Birds Concrete Satellites Earth Feedback pattern recognition Computer architecture Acoustical engineering

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EMG signal estimation based on adaptive wavelet shrinkage for multifunction myoelectric control

EMG signal estimation based on adaptive wavelet shrinkage fo...

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international conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： A. Phinyomark C. Limsakul P. Phukpattaranont Department of Electrical Engineering Faculty of Engineering Songkla University Hatyai Songkhla Thailand

ISBN: (纸本)9781424456062;9789746724913

Electromyography (EMG) signal is interfered with different kinds of noise and wavelet denoising algorithm is a powerful method to reduce noises in EMG signal. Hard and soft shrinkage, traditional wavelet transformation, are applied to wavelet coefficients with threshold value. From the limitation of hard and soft shrinkage, this study proposes nine improved wavelet shrinkage methods that achieve a compromise between two standards. EMG signal from six hand motions with additive noise at different signal-to-noise ratios were applied to evaluate the efficiency of the methods in denoising viewpoint. In addition, features of estimated denoising signal are sent to classification task to measure the performance in myoelectric control. The experimental results show that adaptive wavelet shrinkage method (ADP) provides the better performance than traditional methods and other modified methods in both of denoising and pattern recognition viewpoints. Accuracy of recognition of EMG signal transformed by ADP is improved about 6.5-78.5% depending on the level of noise. ADP is an efficient method for producing useful EMG signal without noise and improving application of myoelectric control.

关键词： Electromyography Estimation Programmable control Adaptive control Noise reduction Wavelet coefficients Additive noise Signal to noise ratio pattern recognition Noise level

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Experimental Comparison of Advance Control Strategies which Use pattern recognition Technique for Nonlinear System

Experimental Comparison of Advance Control Strategies which ...

引用

international conference on Machine Learning and computing

作者： Polaiah Bojja K. Abraham S. Varadarajan M.N. Giri Prasad J.N.T. University Anantapur Andhra Pradesh India Department of Mechanical Engineering ASCET Nellore India S.V. University Tirupati India J.N.T. University Pulivendula India

On-line tool wear estimation in turning is essential for on-line cutting process optimization. In this work, cutting force measurement is used for a reliable on-line flank wear estimation and tool life monitoring. Models for flank wear will be obtained as a function of machining parameters and dynamic cutting forces. The coefficients for flank wear models are obtained by using the experimental results. Then the non-linear dynamic models obtained are calibrated with the actual conditions. These developed models will be used for the simulation of flank wear and using control variable such as cutting speed; the flank wear will be controlled. For model validation, the flank wear is estimated using a non-linear model. In the present work, an attempt has been made to control the flank wear during turning of on-line cutting process using the Fuzzy Logic Controller and Neural network based on self-tuning of PID controller approaches. Those approaches are treat the material as dynamic system and involve developing state space models from available material behavior model. The evaluation of performance criteria can be compared for those approaches of PI controller with Fuzzy Logic Controller and Neural network based on self-tuning of PID controller. Simulation studies are carried-out for the non-linear system using MATLAB software.

关键词： Nonlinear control systems Control systems pattern recognition Nonlinear systems Mathematical model Turning Nonlinear dynamical systems Fuzzy logic Neural networks Three-term control

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