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IAPR International Workshop on Document Analysis Systems, DAS

作者： Martin Lettner Florian Kleber Robert Sablatnig Heinz Miklas Pattern Recognition and Image Processing Group Institute for Computer Aided Automation University of Technology Vienna Vienna Austria Institute for Slavonic Studies University of Technology Vienna Vienna Austria

This paper deals with the enhancement of the readability in historic texts written on parchment. Due to mold, air, humidity, water, etc. parchment and text are partially damaged and consequently hard to read. In order to enhance the readability of the text, the manuscript pages are imaged in different spectral bands ranging from 360 to 1000 nm. The readability enhancement is based on a spectral and spatial analysis of the multivariate image data by multivariate spatial correlation. The main advantage of the method is that especially the text regions are enhanced which is provided by generating a mask image. This mask is based on the automatic reconstruction of the ruling scheme of the text pages. The method is tested on two medieval Slavonic manuscripts written on parchment.

关键词： Multispectral imaging Principal component analysis Degradation image analysis Humidity Spectral analysis Hyperspectral imaging Text analysis pattern analysis pattern recognition

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Extraction of complex wavelet features for iris recognition

Extraction of complex wavelet features for iris recognition

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International Conference on pattern recognition

作者： Xiaofu He Pengfei Shi Department of Computer Science and Technology East China Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shandong Jiaotong University Shanghai China

ISBN: (纸本)9781424421749

This paper presents a new feature extraction method for iris recognition. Since two dimensional complex wavelet transform (2D-CWT) does not only keep wavelet transformpsilas properties of multiresolution decomposition analysis and perfect reconstruction, but also adds its new merits: approximate shift invariance, good directional selectivity for 2-D image, and limited redundancy, which are useful for iris feature extraction. So, a set of high frequency 2D-CWT coefficients are selected as features for iris recognition. The phase information of the coefficients is used for feature encoding and Hamming distance is adopted for classification. Experimental results show that the proposed algorithm can get good recognition rate.

关键词： Iris recognition Feature extraction Wavelet analysis Wavelet transforms image resolution image analysis image reconstruction Two dimensional displays Frequency Encoding

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Multi-view ear recognition based on B-Spline pose manifold construction

Multi-view ear recognition based on B-Spline pose manifold c...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Zhiyuan Zhang Heng Liu Harbin Institute of Technology (HIT)Shenzhen Graduate School Bio-computing Research Center Shenzhen China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

In this work, multi-view ear recognition problems are examined in detail. A new multi-view ear recognition approach based on B-Spline pose manifold construction in discriminative projection space which is formed by null kernel discriminant analysis (NKDA) feature extraction is presented. Many experiments and comparisons are provided to show the effectiveness of our multi-view ear recognition approach.

关键词： Ear Manifolds Spline Feature extraction Principal component analysis Kernel Construction industry

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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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Three Dimensional Palmprint recognition using Structured Light Imaging

Three Dimensional Palmprint Recognition using Structured Lig...

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IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)

作者： David Zhang Guangming Lu Wei Li Lei Zhang Nan Luo Department of Computing Hong Kong Polytechnic University Hong Kong China Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Palmprint is one of the most unique and stable biometric characteristics. Although 2D palmprint recognition can achieve high accuracy, the 2D palmprint images can be easily counterfeited and much 3D depth information is lost in the imaging process. This paper presents a new approach, 3D palmprint recognition, to exploit the 3D structural information of the palm surface. The structured-light imaging is used to acquire the 3D palmprint data, from which the features of Mean Curvature, Gauss Curvature and Surface Type (ST) are extracted. A fast feature matching and score level fusion strategy are then used to classify the input 3D palmprint data. With the established 3D palmprint database, a series of verification and identification experiments are conducted and the results show that 3D palmprint technique can achieve high recognition rate while having high anti-counterfeiting capability.

关键词： image recognition Biometrics Feature extraction Authentication Data mining Counterfeiting image databases Spatial databases Ear Clouds

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Efficient Face Segmentation Based on Face Attention Model and Seeded Region Merging

Efficient Face Segmentation Based on Face Attention Model an...

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9th International Conference on Signal processing(第九届国际信号处理学术会议)(ICSP'08)

作者： Zhi Liu Weiwei Li Xiang Zhang Jie Yang School of Communication and Information Engineering Shanghai UniversityChina Key Lab of Advanced Di School of Communication and Information Engineering Shanghai UniversityChina Institute of Image Processing and Pattern Recognition Shanghai Jiaotong UniversityChina

This paper presents an efficient face segmentation approach based on face attention model and seeded region merging.A face attention model that jointly exploits the information of skin color and eye's position is first constructed to obtain a facial saliency map,which indicates the position of possible faces and is used to determine seed *** a seeded region merging algorithm based on regional facial saliency is proposed to generate a sequence of regions,and the region with the highest regional facial saliency is selected to represent each *** results on a variety of images demonstrate the good segmentation performance of the proposed face segmentation algorithm.

关键词： face segmentation face attention model seeded region merging

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Extracting key postures in a human action video sequence

Extracting key postures in a human action video sequence

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IEEE Workshop on Multimedia Signal processing

作者： Yan Chen Qiang Wu Xiangjian He Chunhua Du Jie Yang Falculty of Information Technology Sydney University of Technology Broadway NSW Australia Falculty of Information Technology University of Technology-Sydney Broadway NSW Australia Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424422944

Human key posture extraction from videos will benefit video storage, video retrieval, human action recognition, human behaviour understanding and so on. This paper presents an approach to select key postures from human action sequences using 2D information. There are two steps in the proposed method. Information measurement which is a kind of global feature of a frame is used to roughly find key posture candidates. Then, a body skeleton feature which is a kind of local feature is applied to select final key postures from the candidates obtained in the first step. The experiments show that the proposed method is efficient.

关键词： Humans Data mining Databases Equations Shape Conferences Distance measurement

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A unifying framework for spectral analysis based dimensionality reduction

A unifying framework for spectral analysis based dimensional...

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International Joint Conference on Neural Networks (IJCNN)

作者： Tianhao Zhang Dacheng Tao Xuelong Li Tie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Biometrics Research Centre Department of Computing Hong Kong Polytechnic University Hong Kong China School of Computer Science and Information Systems University of London UK

Past decades, numerous spectral analysis based algorithms have been proposed for dimensionality reduction, which plays an important role in machine learning and artificial intelligence. However, most of these existing algorithms are developed intuitively and pragmatically, i.e., on the base of the experience and knowledge of experts for their own purposes. Therefore, it will be more informative to provide some a systematic framework for understanding the common properties and intrinsic differences in the algorithms. In this paper, we propose such a framework, i.e., ldquopatch alignmentrdquo, which consists of two stages: part optimization and whole alignment. With the proposed framework, various algorithms including the conventional linear algorithms and the manifold learning algorithms are reformulated into a unified form, which gives us some new understandings on these algorithms.

关键词： Algorithm design and analysis Optimization Spectral analysis Weight measurement Classification algorithms Artificial neural networks Level measurement

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Speckle reduction of SAR images using ICA basis enhancement and separation

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Chinese Optics Letters 2007年第9期5卷 509-512页

作者：李昱彤周越 Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University

An approach for synthetic aperture radar （SAR） image de-noising based on independent component analysis （ICA） basis images is proposed. Firstly, the basis images and the code matrix of the original image are obtained using ICA algorithm. Then, pointwise Hoder exponent of each basis is computed as a cost criterion for basis enhancement, and then the enhanced basis images are classified into two sets according to a separation rule which separates the clean basis from the original basis. After these key procedures for speckle reduction, the clean image is finally obtained by reconstruction on the clean basis and original code matrix. The reconstructed image shows better visual perception and image quality compared with those obtained by other traditional techniques.

关键词： Algorithms image quality Independent component analysis Speckle Synthetic aperture radar

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Dim small targets fusion detection in infrared image

Dim small targets fusion detection in infrared image

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Yu Zheng Jin-Wen Tian Jian Liu School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery of Huazhong University of Science and Technology Wuhan China

To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast threshold. The experimental results show that the method proposed in this paper using wavelet transformation fractal dimension to fuse dual band infrared images, and then detect targets is better than using mid-wave or long -wave infrared images detect targets alone.

关键词： Fractals Wavelet transforms Pixel Object detection Fuses Approximation methods Manganese

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