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Online Text-independent Writer Identification Based on Temporal Sequence and Shape Codes

Online Text-independent Writer Identification Based on Tempo...

引用

International Conference on Document Analysis and recognition

作者： Bangy Li Tieniu Tan Center of Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China

ISBN: (纸本)9781424445004

In this paper we present a novel method for online text-independent writer identification. Most of the existing writer identification techniques require the data to be from a specific text which is not applicable to cases where such text is not available, such as in criminal justice systems when text documents with different content need to be compared. Text-independent approaches often require a large amount of data to be confident of good results. We propose temporal sequence and shape codes to encode online handwriting. Temporal sequence codes (TSC) are to characterize trajectory in speed and pressure change in writing, and shape codes (SC) are to characterize direction of trajectory in writing handwriting. For TSC, we use two different codes to encode speed and pressure to codebook: stroke temporal sequence codes (STSC) and neighbor temporal sequence codes (NTSC). At identification stage, we implement decision and fusion strategy to identify writer. Experimental results show that our proposed method can improve the identification accuracy with a small number of characters. Moreover, we find that the proposed method is even effective for cross-language (English & Chinese) writer identification.

关键词： Shape Writing pattern recognition Text analysis pattern analysis biometrics Data security National security Books Commercialization

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Quality-based dynamic threshold for iris matching

Quality-based dynamic threshold for iris matching

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IEEE International Conference on Image Processing

作者： Wenbo Dong Zhenan Sun Tieniu Tan Zhuoshi Wei Center of Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China

Current iris recognition systems usually regard poor quality iris images useless since defocused or partially occluded iris images may cause false acceptance. However, such a strategy may lose an opportunity to correctly report a genuine match with poor-quality samples. This paper proposes an adaptive iris matching method to improve the throughput of iris recognition systems. The core idea of the method is to dynamically adjust the decision threshold of iris matching module based on the quality measure of input iris image. So that the poor quality iris images also have a chance to match template database under the controlled false accept rate. Experiment results on the real system demonstrate the effectiveness of the proposed method and the recognition time is expected to be greatly reduced.

关键词： Iris recognition Image quality Image recognition Hamming distance Video sequences Throughput Image databases Feature extraction High definition video pattern matching

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Nonnegative Matrix Factorization with Gibbs Random Field modeling

Nonnegative Matrix Factorization with Gibbs Random Field mod...

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Shengcai Liao Zhen Lei Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

In this paper, we present a Gibbs Random Field (GRF) modeling based Nonnegative Matrix Factorization (NMF) algorithm, called GRF-NMF. We propose to treat the component matrix of NMF as a Gibbs random field. Since each component presents a localized object part, as usually expected, we propose an energy function with the prior knowledge of smoothness and locality. This way of directly modeling on the structure of components makes the algorithm able to learn sparse, smooth, and localized object parts. Furthermore, we find that at each update iteration, the constrained term can be processed conveniently via local filtering on components. Finally we give a well established convergence proof for the derived algorithm. Experimental results on both synthesized and real image databases shows that the proposed GRF-NMF algorithm significantly outperforms other NMF related algorithms in sparsity, smoothness, and locality of the learned components.

关键词： Matrix decomposition Sparse matrices Convergence Spectral analysis Clustering algorithms Bayesian methods Conferences biometrics National security Laboratories

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Stepwise Correlation metric based Discriminant Analysis and multi-probe images fusion for face recognition

Stepwise Correlation metric based Discriminant Analysis and ...

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Zhen Lei Shengcai Liao Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

Face recognition is a great challenge in practice. Subspace learning method is one of the dominant methods and has achieved great success in face recognition area. In subspace learning, many researches have found that correlation similarity (e.g. cosine distance) usually achieves better classification results than L2 distance with nearest neighbor (NN) classifier in Euclidean space. However, in traditional methods, most of them are devoted to optimize the objective function based on L2 distance, which is not coincident with the classification rule. It is reasonable to obtain better results by optimizing the objective function with correlation metric directly. In this paper, following traditional linear discriminant analysis (LDA), we redefine the between and with-in class scatter with correlation metric and propose an efficient Stepwise Correlation metric based Discriminant Analysis (SCDA) method to derive the sub-optimal discriminant subspace to be classified with correlation similarity. Moreover, we propose a novel weighted fusion mechanism to learn the optimal combination of multi-probe images to be classified. Extensive experiments on PIE and extended Yale-B databases validate the effectiveness of SCDA and the learning based weighted image fusion method.

关键词： Image analysis Image fusion Face recognition Linear discriminant analysis Learning systems Nearest neighbor searches Neural networks Optimization methods Scattering Image databases

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A Set theoretical method for video synopsis

A Set theoretical method for video synopsis

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1st International ACM Conference on Multimedia Information Retrieval, MIR2008, Co-located with the 2008 ACM International Conference on Multimedia, MM'08

作者： Xu, Min Li, Stan Z. Li, Bin Yuan, Xiao-Tong Xiang, Shi-Ming Dept. of Electronic Science and Technology University of Science and Technology of China Hefei China Biometrics and Security Research National Laboratory of Pattern Recognition CASIA Beijing China

ISBN: (纸本)9781605583129

A synopsis video presents a condensed video activities occurring during different periods, based on moving objects extracted in the spatial-temporal domain. How to place different object tubes with least collision in limited video length is crucial to synopsis performance but has not been thoroughly studied in previous work. In this paper, we address an important problem in video synopsis, that of object start-time programming. We formulate the problem in terms of set theory. An objective is derived to maximize visual information in video synopsis. After relaxing the problem to obtain a continuous one, the problem can be efficiently solved via mean-shift. The resulting algorithm can converge to the local optimum within a few iterations. Copyright 2008 ACM.

关键词： Set theory

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Counterfeit iris detection based on texture analysis

Counterfeit iris detection based on texture analysis

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作者： Wei, Zhuoshi Qiu, Xianchao Sun, Zhenan Tan, Tieniu Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation P.O. Box 2728 Beijing 100190 China

ISBN: (纸本)9781424421756

This paper addresses the issue of counterfeit iris detection, which is a liveness detection problem in biometrics. Fake iris mentioned here refers to iris wearing color contact lens with textures printed onto them. We propose three measures to detect fake iris: measuring iris edge sharpness, applying Iris-Texton feature for characterizing the visual primitives of iris textures and using selected features based on co-occurrence matrix (CM). Extensive testing is carried out on two datasets containing different types of contact lens with totally 640 fake iris images, which demonstrates that Iris-Texton and CM features are effective and robust in anticounterfeit iris. Detailed comparisons with two stateof- the-art methods are also presented, showing that the proposed iris edge sharpness measure acquires a comparable performance with these two methods, while Iris-Texton and CM features outperform the state-of-the-art. © 2008 IEEE.

关键词： Contact lenses

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Technology roadmap for smart Iris recognition

Technology roadmap for smart Iris recognition

引用

18th International Conference on Computer Graphics and Vision, GraphiCon 2008

作者： Sun, Zhenan Dong, Wenbo Tan, Tieniu Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences P.O. Box 2728 Beijing 100190 China

Iris recognition has many desirable properties for reliable individual authentication but usability is its largest bottleneck to wide deployment. Thus smart interface and machine intelligent are the objective of next-generation iris recognition. This paper presents the technology roadmap for smart iris recognition (SIR). Firstly, the concept of SIR is introduced, including its definition, characteristics and performance target. Then the evolution process of iris acquisition and recognition algorithm is proposed respectively. With various strategies of human-machine interaction, iris acquisition systems are grouped into seven categories, i.e. Close-range IR, Active IR, IR at a distance, Active IR at a distance, Passive IR on move, Active IR on move, IR for Surveillance. Iris recognition algorithms advance to be more accurate, robust, efficient and secure. The achievements of state-of-the-art iris recognition methods especially the contributions of our research group are reviewed in the roadmap.

关键词： biometrics

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Synthesis of large realistic iris databases using patch-based sampling

Synthesis of large realistic iris databases using patch-base...

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作者： Wei, Zhuoshi Tan, Tieniu Sun, Zhenan Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation P.O. Box 2728 Beijing 100190 China

ISBN: (纸本)9781424421756

This paper presents a framework to synthesize large realistic iris databases, providing an alternative to iris database collection. Firstly, iris patch is used as a basic element to characterize visual primitive of iris texture, and patch-based sampling is applied to create an iris prototype. Then a set of pseudo irises with intra-class variations are derived from the prototype. Qualitative and quantitative studies reveal that synthetic databases are well suited for evaluating iris recognition systems by achieving three goals: (1) the synthetic iris images bear a close resemblance to real iris images in terms of visual appearance;(2) the proposed framework is able to generate databases with large capacity;(3) statistical performance shows that the synthetic iris images hold all the major characteristics of real iris images. © 2008 IEEE.

关键词： Database systems

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Gabor volume based local binary pattern for face representation and recognition

Gabor volume based local binary pattern for face representat...

引用

International Conference on Automatic Face and Gesture recognition

作者： Zhen Lei Shengcai Liao Ran He Matti Pietikainen Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Chinese Academy of Sciences Beijing China Machine Vision Group University of Oulu Oulun yliopisto FI Finland

This paper presents a novel face representation and recognition approach. The face image is first decomposed by multi-scale and multi-orientation Gabor filters and local binary pattern (LBP) analysis is then applied on the derived Gabor magnitude responses. Different from (W.C. Zhang et al., 2005), the present method not only describes the neighboring relationship in spatial domain, but also exploit those between different scales (frequency) and orientations. Specifically, we first reformulate the Gabor magnitude responses as a 3rd-order volume and then apply LBP analysis on three orthogonal planes of the Gabor volume, named GV-LBP-TOP in short, in a hope to encode sufficient information for face representation. Further, a computationally effective version, E-GV-LBP, is proposed to depict the neighboring changes in spatial, frequency and orientation domains simultaneously. Finally, the weighted histogram intersection metric is utilized to measure the dissimilarity of faces. Experimental results on FERET and FRGC ver 2.0 databases show the significant advantages of the proposed method.

关键词： Face recognition pattern recognition Histograms Principal component analysis Independent component analysis Lighting Face detection Linear discriminant analysis Robustness Gabor filters

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A hierarchical model for the evaluation of biometric sample quality

A hierarchical model for the evaluation of biometric sample ...

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作者： He, Qian Sun, Zhenan Tan, Tieniu Zou, Yong National Laboratory of Pattern Recognition Center for Biometrics Authentication and Testing Chinese Academy of Sciences P.O. Box 2728 Beijing 100190 China

ISBN: (纸本)9781424421756

The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This model is developed on the basis of three types of influencing factors: global factors, subjective factors and variable factors. We adopt different strategies to compute the corresponding three level qualities: database level quality, class level quality and image level quality. The database level quality is estimated by experience. Then, we compute the mean value of variable number of normalized genuine scores, the quantiles of which are used to determine the class level quality. On the image level quality evaluation, a novel concept of subset frequency is proposed. © 2008 IEEE.

关键词： biometrics

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