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License recognition based on image processing

License recognition based on image processing

引用

international conference on Networked computing (INC)

作者： Xiaoping Li Lin Zhang Yinxiang Li Xiaoxing Lv Jianqiang Xu Yuhuan Jing Beijing Institute of Technology Beijing China

ISBN: (纸本)9781424469864;9788988678206

With the microprocessor as its core, the license plate automatic recognition system is a highly intelligent electronic system based on technologies such as image processing and pattern recognition. This paper focuses on the preprocessing before license plate recognition after locating the license plate. This paper comprehensively utilizes kinds of image processing, image analyzing and mode recognition technologies, drawing lessons from parts of the previous research achievements in this field and making some improvement. This paper designs and finally realizes the thinning algorithm which combines the advantages of Medial Axis Transform and Peeling Method, and Multi-state Neural Network Algorithm, which greatly increases the recognition efficiency of the system and reaches the goal of putting the system into practical use.

关键词： Licenses Image recognition Image processing pattern recognition Algorithm design and analysis Image segmentation Character recognition Neural networks Image sensors Vehicles

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Text, Speech and Dialogue - 13th international conference, TSD 2010, Proceedings

Text, Speech and Dialogue - 13th International Conference, T...

引用

13th international conference on Text, Speech and Dialogue, TSD 2010

ISBN: (纸本)3642157599

The proceedings contain 74 papers. The topics discussed include: towards disambiguation of word sketches;these nouns that hide events: an initial detection;extracting human Spanish nouns;semantic duplicate identification with parsing and machine learning;comparison of different lemmatization approaches through the means of information retrieval performance;real anaphora resolution is hard: the case of German;event-time relation identification using machine learning and rules;question answering for not yet semantic web;semantic role patterns and verb classes in verb valency lexicon;opinion mining by transformation-based domain adaptation;improving automatic image captioning using text summarization techniques;automatic sentiment analysis using the textual pattern content similarity in natural language;diagnostics for debugging speech recognition systems;and automatic lip reading in the Dutch language using active appearance models on high speed recordings.

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EMD strategy for activation detection in functional MRI of the human brain

EMD strategy for activation detection in functional MRI of t...

引用

2010 international conference on Computer Application and System Modeling, ICCASM 2010

作者： Zheng, Tianxiang Yang, Lihua Jiang, Tianzi Department of Tourism Management Shenzhen Tourism College Jinan University Shenzhen China Department of Scientific Computing and Computer Application School of Mathematics and Computational Science Sun Yat-sen University Guangzhou China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424472369

This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to activation detection in task-related functional Magnetic Resonance Imaging (fMRI) of the human brain. The method is illustrated using fMRI data simulated under one paradigm as well as one real dataset, and its performance is compared to those of a leading model based (General Linear Model - GLM) and a leading data-driven (Region Growing Method - RGM) approach. It is concluded that the proposed method achieves much better performance than the computationally inefficient RGM and is slightly more sensitive than GLM. Experimental results support its efficiency and sensitivity, which indicates that it is to become a viable alternative to the fMRI analysis. © 2010 IEEE.

关键词： Empirical mode decomposition

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A novel, smart and fast searching method for star pattern recognition using star magnitudes

A novel, smart and fast searching method for star pattern re...

引用

international conference on Image and Vision computing New Zealand, IVCNZ

作者： SH. Sohrabi A.A. Beheshti Shirazi E-Iearning Center Iran University of Science and Technology Iran Electrical Engineering Iran University of Science and Technology Iran

The key performances of the star pattern recognition algorithms are the identification efficiency and the time consumed. In the past decades, much effort has been made, and lots of them are made out. To reduce the computations database search and star features extraction time and increasing the accuracy of star pattern recognition algorithm a novel, smart and fast star identification algorithm by using star magnitudes is proposed. The simulation results based on the Desktop Universes images show that the proposed star identification and database search algorithm can achieve both high accuracy and fast recognition. The database search and star features extraction time is O(n). In addition to, since the quality of star images play an important role in improving accuracy of star pattern recognition algorithm, therefore for image pre-processing we propose a fuzzy edge detection technique. This method highly affects noise cancellation, star features extraction, database production and matching algorithm.

关键词： Feature extraction Databases Space vehicles Hardware Shape pattern matching

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Multi-class pattern Classification in Imbalanced Data

Multi-class Pattern Classification in Imbalanced Data

引用

international conference on pattern recognition

作者： Amal S. Ghanem Svetha Venkatesh Geoff West Department of Computing University of Bahrain Bahrain Department of Computing Curtin University of Technology Perth WA Australia

ISBN: (纸本)9781424475421

The majority of multi-class pattern classification techniques are proposed for learning from balanced datasets. However, in several real-world domains, the datasets have imbalanced data distribution, where some classes of data may have few training examples compared for other classes. In this paper we present our research in learning from imbalanced multi-class data and propose a new approach, named Multi-IM, to deal with this problem. Multi-IM derives its fundamentals from the probabilistic relational technique (PRMs-IM), designed for learning from imbalanced relational data for the two-class problem. Multi-IM extends PRMs-IM to a generalized framework for multi-class imbalanced learning for both relational and non-relational domains.

关键词： Training data Glass pattern recognition Probabilistic logic Training Artificial neural networks Testing

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Research on the Application of pattern Selection Algorithm in Bioinformatic Data Bases on Mutual Information

Research on the Application of Pattern Selection Algorithm i...

引用

international conference on Pervasive computing Signal Processing and Applications (PCSPA)

作者： Xin Li Wenxue Hong Chun Zhao Institute of Biomedical Engineering Yanshan University슠 Qinhuangdao China

pattern selection is an important part in the research fields of data mining and pattern recognition, especially for the high-dimensional data in the Bioinformatics. In this paper, a new pattern selection algorithm was proposed to finish pattern selection bases on Mutual Information. pattern subset evaluation index was researched to ensure the best feature subset was selected. The algorithm bases on the correlation of patterns and label, as well as the redundancy between the patterns. Fuzzy pattern Subset Evaluation Index was researched to make sure which is the best subset for the pattern subset evaluation. To verify the effectiveness of the method, some experiments were finished with the data of gene expression data (Leiden University) and UCI datasets. The experimental results indicate that the algorithm achieved better results.

关键词： Redundancy Indexes Classification algorithms Mutual information Bioinformatics pattern recognition Gene expression

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Experimental comparison of advance control strategies which uses pattern recognition technique for nonlinear system

Experimental comparison of advance control strategies which ...

引用

2010 The 2nd international conference on Machine Learning and computing, ICMLC 2010

作者： Bojja, Polaiah Abraham, K. Varadarajan, S. Giri Prasad, M.N. J.N.T. University Ananthapur A..P India Dept. of Mechanical Engg. ASCET Nellore India S.V. University Tirupati India J.N.T. University Pulivendula India

ISBN: (纸本)9780769539775

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 nonlinear 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 nonlinear system using MATLAB software. © 2010 IEEE.

关键词： Nonlinear systems

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Periocular region appearance cues for biometric identification

Periocular region appearance cues for biometric identificati...

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IEEE Computer Society conference on Computer Vision and pattern recognition Workshops (CVPRW)

作者： Damon L. Woodard Shrinivas J. Pundlik Jamie R. Lyle Philip E. Miller Biometrics and Pattern Recognition Lab School of Computing Clemson University Clemson SC USA

We evaluate the utility of the periocular region appearance cues for biometric identification. Even though periocular region is considered to be a highly discriminative part of a face, its utility as an independent modality or as a soft biometric is still an open ended question. It is our goal to establish a performance metric for the periocular region features so that their potential use in conjunction with iris or face can be evaluated. In this approach, we employ the local appearance based feature representation, where the image is divided into spatially salient patches, and histograms of texture and color are computed for each patch. The images are matched by computing the distance between the corresponding feature representations using various distance metrics. We report recognition results on images captured in the visible and near-infrared (NIR) spectrum. For the color periocular region data consisting of about 410 subjects and the NIR images of 85 subjects, we obtain the Rank-1 recognition rate of 91% and 87% respectively. Furthermore, we also demonstrate that recognition performance of the periocular region images is comparable to that of face.

关键词： Biometrics Iris Face recognition Image recognition Skin Facial features Measurement Humans Eyes Feature extraction

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Biometric personal identification based on iris pattern recognition using Wavelet Packet Transform

Biometric personal identification based on iris pattern reco...

引用

international conference on computing and Networking Technology (ICCNT)

作者： S. Hariprasath V. Mohan Saranathan College of Engineering Tiruchirapalli India

A new iris recognition system based on Wavelet Packet Analysis and Morlet wavelet is described. Morlet wavelet calculations are easy compared to Gabor wavelets. Moreover Gabor wavelet based iris recognition system is patented which blocks its further development. The most unique phenotypic feature visible in a person's face is the detailed texture of each eye's iris. The visible texture of a person's iris is encoded into a compact sequence of 2-D Morlet wavelet coefficients, which generate an “iris code” of 4096-bits. Two different iris codes are compared using exclusively OR comparisons. In this paper, we propose a novel multi-resolution approach based on Wavelet Packet Transform (WPT) for iris texture analysis and recognition. The development of this approach is motivated by the observation that dominant frequencies of iris texture are located in the low and middle frequency channels. With an adaptive threshold, WPT sub images coefficients are quantized into 1, 0 or -1 as iris signature. This signature presents the local information of different irises. The signature of the new iris pattern is compared against the stored pattern after computing the signature of new iris pattern and identification is performed.

关键词： Iris recognition Iris Feature extraction Wavelet packets Wavelet analysis

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recognition of Faces Using Improved Principal Component Analysis

Recognition of Faces Using Improved Principal Component Anal...

引用

international conference on Machine Learning and computing

作者： E. Gomathi K. Baskaran Department of ECE Karpagam College of Engineering Coimbatore India Department of ECE Government College of Technology Coimbatore India

Face recognition has been an important issue in computer vision and pattern recognition over the last several decades. While a human can recognize faces easily, automated face recognition remains a great challenge in computer-based automated recognition research. One difficulty in face recognition is how to handle the variations in expression, pose, and illumination when only a limited number of training samples are available. In this paper, an Improved Principal Component Analysis (IPCA) is proposed for face recognition. Initially the eigenspace is created with eigenvalues and eigenvectors. From this space, the eigenfaces are constructed, and the most relevant eigenfaces have been selected using IPCA. With these eigenfaces, the input images are be classified based on Euclidian distance. The proposed method was tested on ORL face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

关键词： Face recognition Principal component analysis Face detection Image databases Computer vision pattern recognition Humans Lighting Eigenvalues and eigenfunctions Testing

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