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检索条件"机构=Institute of Pattern Recognition & Image Processing"

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Ancient document analysis based on text line extraction

Ancient document analysis based on text line extraction

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作者： Kleber, Florian Sablatnig, Robert Gau, Melanie Miklas, Heinz Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology 1040 Vienna Austria Institute for Slavonic Studies University of Vienna 1010 Vienna Austria

ISBN: (纸本)9781424421756

In order to preserve our cultural heritage and for automated document processing libraries and national archives have started digitizing historical documents. In the case of degraded manuscripts (e.g. by mold, humidity, bad storage conditions) the text or parts of it can disappear. The remaining parts of the text can be segmented and the ruling can be extrapolated with the a priori knowledge. Since the ruling defines the position of the text within a page, it can be used for layout analysis and as a basis for the enhancement of the readability. Furthermore, information about the scribe (hand) of the manuscript, its spatiotemporal origin can be gained by analyzing the ruling. This paper presents an algorithm for ruling estimation of Glagolitic texts based on text line extraction and is suitable for degraded manuscripts by extrapolating the baselines with the a priori knowledge of the ruling. The algorithm was tested on 30 pages of the Missale Sinaiticum and the evaluation was based on visual criteria. © 2008 IEEE.

关键词： Extrapolation

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Registration and enhancing of multispectral manuscript images

Registration and enhancing of multispectral manuscript image...

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16th European Signal processing Conference, EUSIPCO 2008

作者： Lettner, Martin Diem, Markus Sablatnig, Robert Miklas, Heinz Pattern Recognition and Image Processing Group Institute for Computer Aided Automation Vienna University of Technology 1040 Vienna Austria Institute for Slavonic Studies University of Vienna 1010 Vienna Austria

Two medieval manuscripts are recorded, investigated and analyzed by philologists in collaboration with computer scientists. Due to mold, air humidity and water the parchment is 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 1000nm. A registration process is necessary for further image processing methods which combine the information gained by the different spectral bands. Therefore, the images are coarsely aligned using rotationally invariant features and an affine transformation. Afterwards, the similarity of the different images is computed by means of the normalized cross correlation. Finally, the images are accurately mapped to each other by the local weighted mean transformation. The algorithms used for the registration and results in enhancing the texts using Multivariate Spatial Correlation are presented in this paper. copyright by EURASIP.

关键词： image enhancement

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Semi-supervised marginal discriminant analysis based on QR decomposition

Semi-supervised marginal discriminant analysis based on QR d...

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International Conference on pattern recognition

作者： Rui Xiao Pengfei Shi Institute of Image Processing and Pattern Recognition Shandong Jiaotong University

ISBN: (纸本)9781424421749

In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neighborhood relations between the data points from the same class, while maximizing the margin between the neighboring data points with different class labels. Different from traditional dimensionality reduction algorithms like linear discriminant analysis (LDA) and maximum margin criterion (MMC) which seeks only the global Euclidean structure, SMDA takes local structure of the data into account. Moreover, it is designed for semi-supervised learning which incorporates both labeled and unlabeled data points and avoids suffering the small sample size (SSS) problem. QR decomposition is then employed to find the optimal transformation which makes the algorithm scalable and more efficient. Experiments on face recognition are presented to show the effectiveness of the method.

关键词： Linear discriminant analysis Principal component analysis image analysis pattern analysis pattern recognition Semisupervised learning Face recognition Performance analysis Scattering Matrix decomposition

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A fake iris detection method based on FFT and quality assessment

A fake iris detection method based on FFT and quality assess...

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2008 Chinese Conference on pattern recognition, CCPR 2008

作者： He, Xiaofu Lu, Yue Shi, Pengfei Department of Computer Science and Technology East China Normal University Shanghai 200241 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424423163

In recent years, iris recognition is becoming a very active topic in both research and practical applications. However, fake iris is a potential threat there are potential threats for iris-based systems. This paper presents a novel fake iris detection method based on the analysis of 2-D Fourier spectra together with iris image quality assessment. First, image quality assessment method is used to exclude the defocused, motion blurred fake iris. Then statistical properties of Fourier spectra for fake iris are used for clear fake iris detection. Experimental results show that the proposed method can detect photo iris and printed iris effectively. ©2008 IEEE.

关键词： Biometrics

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The projective equation of a circle and its application in camera calibration

The projective equation of a circle and its application in c...

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International Conference on pattern recognition

作者： Yinqiang Zheng Yuncai Liu Image Processing and Pattern Recognition Institute Shandong Jiaotong University China

ISBN: (纸本)9781424421749

In this article, we present the projective equation of a circle in a perspective view, which naturally encodes such important geometric entities as the projected circle center, the vanishing point of the normal direction of the circlepsilas supporting plane and the degenerate conic envelope spanned by the image of circular points (ICPs). Based on this projective equation, we propose an easy technique to calibrate the focal length and the extrinsic parameters of a camera merely by using one perspective view of two arbitrary coplanar circles. Unlike existing optimization algorithm, our method offers a closed form solution through simple matrix manipulation. Experimental results verify the correctness and efficiency of our proposed technique.

关键词： Equations Cameras Calibration Transmission line matrix methods Optimization methods Closed-form solution Iterative algorithms image processing pattern recognition Iterative methods

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A novel classifier for handwritten numeral recognition

A novel classifier for handwritten numeral recognition

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Ying Wen Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

This paper presents a novel pattern classification approach- a kernel and Bhattacharyya distance based classifier which utilizes the distribution characteristics of the samples in each class. Bhattacharyya distance in the subspace spanned by the eigenvectors which are associated with the smaller eigenvalues in each class is adopted as the classification criterion. The smaller eigenvalues are substituted by a small value threshold in such a way that the classification error in a given database is minimized. Application of the proposed classifier to the issue of handwritten numeral recognition demonstrates that it is promising in practical applications.

关键词： Handwriting recognition Kernel Covariance matrix Eigenvalues and eigenfunctions Principal component analysis pattern classification Databases Gaussian distribution Character recognition pattern recognition

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Deformable surface stereo tracking-by-detection using Second Order Cone Programming.

Deformable surface stereo tracking-by-detection using Second...

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International Conference on pattern recognition

作者： Shuhan Shen Yinqiang Zheng Yuncai Liu Institute of Image Processing and Pattern Recognition Shandong Jiaotong University China

ISBN: (纸本)9781424421749

We present a method for tracking deformable surfaces in 3D using a stereo rig. Different from traditional recursive tracking approaches that provide a strong prior on the pose for each new frame, the proposed method tracks deformable surfaces by detecting them in individual frames. In our method, the model of the surface is represented by a triangulated mesh. The constraints for model to image keypoint correspondences, together with the constraints that preserve the lengths of mesh edges, are formulated as second order cone programming (SOCP) constraints, leading this tracking-by-detection method to be an SOCP problem that can be effectively solved. Experiments on a piece of deformed paper demonstrate the capability of the proposed tracking-by-detection method.

关键词： image edge detection Deformable models image processing pattern recognition Visual servoing Augmented reality image sequences image reconstruction Shape Layout

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Practical multi-camera calibration algorithm with 1D objects for virtual environments

Practical multi-camera calibration algorithm with 1D objects...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zijian Zhao Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

A new calibration algorithm for multi-camera systems using the 1D calibration objects is proposed. The algorithm integrates the rank-4 factorization with Zhangpsilas method. The intrinsic parameters as well as the extrinsic parameters are recovered only by capturing with cameras the 1D objectpsilas rotations around a fixed point. The algorithm is based on factorization of the scaled measurement matrix, the projective depths of which is estimated in an analytic equation instead of a recursive form. For the conditions that there are more than 3 points on the 1D object, our algorithm may solve them by extending the scaled measurement matrix. The obtained parameters are finally refined through the maximum likelihood inference. The validity of the proposed technique was verified through simulation and experiments with real images.

关键词： Cameras Calibration Transmission line matrix methods Equations Matrix decomposition Mathematical model Shape

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Probability Evolutionary Algorithm based human motion tracking using voxel data

Probability Evolutionary Algorithm based human motion tracki...

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Congress on Evolutionary Computation

作者： Shuhan Shen Haolong Deng Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

A novel evolutionary algorithm called probability evolutionary algorithm (PEA), and a method based on PEA for visual tracking of human body using voxel data are presented. PEA is inspired by the quantum computation and the quantum-inspired evolutionary algorithm, and it has a good balance between exploration and exploitation with very fast computation speed. The individual in PEA is encoded by the probabilistic compound bit, defined as the smallest unit of information, for the probabilistic representation. The observation step is used in PEA to obtain the observed states of the individual, and the update operator is used to evolve the individual. In the PEA based human tracking framework, tracking is considered to be a function optimization problem, so the aim is to optimize the matching function between the model and the image observation. Since the matching function is a very complex function in high-dimensional space, PEA is used to optimize it. Experiments on 3D human motion tracking using voxel data demonstrate the effectiveness, significance and computation efficiency of the proposed human tracking method.

关键词： Humans Tracking Probabilistic logic Three dimensional displays Evolutionary computation Solid modeling Computational modeling

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A New image Quality Approach Based on Decision Fusion

A New Image Quality Approach Based on Decision Fusion

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Mingna Liu Xin Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

image quality evaluation is becoming essential in many image processing problems. This paper proposes a new image quality evaluation approach based on decision fusion method of canonical correlation analysis (CCA). By exploring several diverse visual models, we constructed a comprehensive quality metric which can deal with complicated image distortion problem with increasing accuracy and robustness. Validation by comparing the proposed metric against other image quality metrics (IQMs) demonstrates that its fidelity prediction performs better across wide distortion range and types.

关键词： image quality image processing Robustness image databases image analysis Testing Spatial databases Visual databases Accuracy Fuzzy systems

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