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Fingerprint ridge line extraction based on tracing and directional feedback

引用

International conference on Computational Intelligence and Security

作者： Ma, R Qi, YX Zhang, CS Wang, JX Tsing Hua Univ State Key Lab Intelligent Technol & Syst Dept Comp Sci Beijing 100084 Peoples R China Tsing Hua Univ Res Inst Informat Technol Network Secur Lab Beijing 100084 Peoples R China Tsing Hua Univ State Key Lab Intelligent Technol & Syst Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)3540308180

Fingerprint recognition and verification are always the key issues in intelligent technology and information security. Extraction of fingerprint ridge lines is a critical pre-processing step in fingerprint identification applications. Although existing algorithms for fingerprint extraction work well on good-quality images. Their performance decrease when handling poor-quality images. This paper addresses the ridge line extraction problem as curve tracking processes under the framework of probabilistic tracking. Each ridge line is modeled as sequential frames of a continuous curve and then traced by standard CONDENSATION algorithm in the area of computer vision. Additionally, local directional image is rectified with a feedback technique after each tracking step to improve the accuracy. The experimental results are compared with those obtained through existing well-known algorithms, such as local-binarization and sampling-tracing methods. In spite of greater computational complexity, the method proposed performs better both in terms of efficiency and robustness.

关键词： pattern recognition

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Factors of overtraining with fuzzy ARTMAP neural networks

Factors of overtraining with fuzzy ARTMAP neural networks

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International Joint conference on Neural Networks (IJCNN)

作者： P. Henniges E. Granger R. Sabourin Département de génie de la Production Automatisée Laboratoire d'imagerie de vision et d'intelligence artificielle École de technologie supérieure Montreal QUE Canada

In this paper, the impact of overtraining on the performance of fuzzy ARTMAP neural networks is assessed for pattern recognition problems consisting of overlapping class distributions, and consisting of complex decision boundaries with no overlap. computer simulations are performed with fuzzy ARTMAP networks trained for one epoch, through cross-validation, and until network convergence, using several data sets representing these pattern recognition problems. By comparing the generalisation error and resources required by these networks, the extent of overtraining due to factors such as data set structure, training strategy, number of training epochs, data normalisation, and training set size, is demonstrated. A significant degradation in fuzzy ARTMAP performance due to overtraining is shown to depend on the training set size and the number of training epochs for pattern recognition problems with overlapping class distributions.

关键词： Fuzzy neural networks Neural networks Fuzzy sets pattern recognition computer simulation Subspace constraints Convergence computer errors Supervised learning Handwriting recognition

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Research on Remote Meter Automatic Reading Based on computer vision

Research on Remote Meter Automatic Reading Based on Computer...

引用

ieee/PES Transmission and Distribution conference and Exhibition: Asia and Pacific

作者： Shutao Zhao Baoshu Li Jinsha Yuan Guiyan Cui Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control under Ministry of Education North China Electric Power University Baoding Hebei China Electrical Communication Department North China Electric Power University Baoding Hebei China North China Electric Power University Baoding Hebei China

A novel method is put forward, which the power meter can be read based on compute vision, and the architecture of remote meter auto reading system is designed. Different with the normal automatic meter reading system that must obtain the value from digital communication interface, the new method recognizes the meter reading utilizing the computer vision technique, it is a kind of non-contact measurement. In the meter automatic reading, the computer vision discrimination, incorporate human's ability of visual and apprehensive models. Not only the digital display power meter can be read, but also the direct-reading instrument can be fetched. In this paper, the scheme of remote automatic reading is introduced, the local meter reading information of distributed substation can be transmitted to center using computer network and then the pretreatment, segmentation and pattern matching, are detailed description in the meter image recognition process. Via energy meter automatic recognition experiment, the results based computer vision is accurate enough to monitor the remote substation running parameters

关键词： computer vision Meter reading Substations computer architecture Automatic meter reading Digital communication Power system modeling computer displays Instruments computer networks

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Viewpoint invariant sign language recognition

Viewpoint invariant sign language recognition

引用

ieee International conference on Image Processing

作者： Qi Wang Xilin Chen Liangguo Zhang Chunli Wang Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China Institute of Computing Technology Chinese Academy of Sciences China

Sign language is the primary modality of communication among deaf and mute society all over the world. This paper proposes a viewpoint independent method for sign recognition. Considering that two sequences of the same sign can be roughly considered as the input of a stereo vision system after time-warping, and the fundamental matrix associated with two views should be unique, we can convert the temporal-spatial recognition task as a verification task within a stereo vision framework. After time-warping of the input sequences, the proposed framework can reach both temporal and viewpoint invariance. We demonstrate the efficiency of the proposed framework by recognizing a vocabulary of 100 words of Chinese sign language. The recognition rate is up to 97% at rank 3. Furthermore, the proposed framework can be easily extended to other recognition tasks, such as gait recognition and lip-reading recognition.

关键词： Handicapped aids Cameras Stereo vision Hidden Markov models Vocabulary Deafness Data gloves Testing computer science Content addressable storage

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Video behaviour profiling and abnormality detection without manual labelling

Video behaviour profiling and abnormality detection without ...

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International conference on computer vision (ICCV)

作者： Tao Xiang Shaogang Gong Department of Computer Science Queen Mary University of London London UK

A novel framework is developed for automatic behaviour profiling and abnormality sampling/detection without any manual labelling of the training dataset. Natural grouping of behaviour patterns is discovered through unsupervised model selection and feature selection on the eigenvectors of a normalised affinity matrix. Our experiments demonstrate that a behaviour model trained using an unlabelled dataset is superior to those trained using the same but labelled dataset in detecting abnormality from an unseen video

关键词： Labeling Layout Sampling methods pattern recognition Robustness Humans Feature extraction computer science Prototypes Bayesian methods

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A normalization based image affine estimation technique for computer vision

A normalization based image affine estimation technique for ...

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ieee/ASME (AIM) International conference on Advanced Intelligent Mechatronics

作者： Hwan Il Kang Seungchul Lim Kab Il Kim Young Ik Son Department of Information Eng. Myongji University Yongin si Gyeonggi South Korea Department of Mechanical Eng. Myongji University Yongin si Gyeonggi South Korea Department of Electrical Eng. Myongji University Yongin si Gyeonggi South Korea

In this paper, we propose the estimation method for the image affine information for computer vision. The first estimation method is given based on the XYS image normalization and the second estimation method is based on the XSR image normalization. In addition, we show that rotation and aspect ratio information can be obtained using the central moments of both the original image and the sensed image. Finally, we propose the modified version of the normalization method so that we may control the size of the image. It turns out that the XYS method has much better performance than the XSR method for the image having the aspect ratio change

关键词： computer vision Matrix decomposition Size control pattern recognition Anisotropic magnetoresistance Helium Digital images Mechatronics USA Councils

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Image segmentation applications with unsupervised neural networks

Image segmentation applications with unsupervised neural net...

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ieee Signal Processing and Communications Applications (SIU)

作者： A. Sengur I. Turkoglu M. Cevdet Ince Bilgisayar ve Elektronik Eğitimi Bölümü Fırat Üniversitesi Elazig Turkey Elektrik ve Elektronik Mühendisliği Bölümü Fırat Üniversitesi Elazig Turkey

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Six color separation using the additional colorants with less dot visibility

Six color separation using the additional colorants with les...

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STOC'05: Proceedings of the 37th Annual ACM Symposium on Theory of Computing

作者： Son, Chang-Hwan Cho, Yang-Ho Park, Kee-Hyon Ha, Yeong-Ho School of Electrical Engineering and Computer Science Kyungpook National University Taegu Korea Republic of Department of Electronic Engineering Kyungpook National University IEEE Taegu Section IEEE Pattern Recognition Society Society for IS and T

This paper proposes a method of six-color separation using additional colorants with less dot visibility to reduce the color difference and graininess. In conventional six-color separation, the use of light magenta and light cyan is generally an effective way of reducing the visibility of dots in bi-level printing devices, i.e., light magenta and light cyan are used in a bright region instead of magenta and cyan. However, the hue values for light magenta and light cyan differ from those for magenta and cyan in CIELAB space, making the colorimetric reproduction less inaccurate. Therefore, to minimize this inaccuracy, the proposed method uses yellow and light magenta colorants as additional colorants. In a bright region, magenta is replaced with light magenta and yellow, while cyan is replaced with light cyan and light magenta. These combinations reduce the hue difference, as they create colors with a similar hue to magenta and cyan. In addition, a smooth image can be simultaneously obtained due to the lower dot visibility of the additional colorants. In a middle region, magenta is replaced with light magenta and magenta, while cyan is replaced with light cyan and cyan. Since the use of these two colorants with different concentrations makes a coarse dot pattern, this phenomenon is reflected based on a quantitative granularity metric. Finally, in a dark region, only the magenta and cyan colorants are used as usual. Experiments show that the proposed method can simultaneously produce a colorimetric and smooth-tone reproduction.

关键词： Color image processing

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Geometric invariants and applications under catadioptric camera model

Geometric invariants and applications under catadioptric cam...

引用

International conference on computer vision (ICCV)

作者： Yihong Wu Zhanyi Hu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

This paper presents geometric invariants of points and their applications under central catadioptric camera model. Although the image has severe distortions under the model, we establish some accurate projective geometric invariants of scene points and their image points. These invariants, being functions of principal point, are useful, from which a method for calibrating the camera principal point and a method for recovering planar scene structures are proposed. The main advantage of using these in variants for plane reconstruction is that neither camera motion nor the intrinsic parameters, except for the principal point, is needed. The theoretical correctness of the established invariants and robustness of the proposed methods are demonstrated by experiments. In addition, our results are found to be applicable to some more general camera models other than the catadioptric one

关键词： Cameras Solid modeling Robot vision systems Equations Optical distortion Image reconstruction Layout Mirrors Calibration computer vision

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Neural network-based shape recognition using generalized differential evolution training algorithm

Neural network-based shape recognition using generalized dif...

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International Joint conference on Neural Networks (IJCNN)

作者： Ji-Xiang Du De-Shuang Huang Xiao-Feng Wang Xiao Gu Department of Automation University of Science and Technology China Intelligent Computing Lab Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China

In this paper a new method for recognition of 2D occluded shapes based on neural network using generalized differential evolution training algorithm is proposed. Firstly, a generalized differential evolution (GDE) algorithm is introduced. And this GDE algorithm is applied to train multilayer perceptron neural networks. Then a new shape feature, refer to as multiscale Fourier descriptors (MFDs) is proposed. Finally, the superiority of GDE training method over traditional approaches to train networks is demonstrated by experiment. The experimental results show that our proposed GDE training method is much efficient and effective. And they also showed that the MFDs method is suitable for the shape recognition.

关键词： Neural networks Shape Genetic algorithms Image recognition Artificial neural networks Machine intelligence pattern recognition Fourier transforms Genetic mutations computer vision

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