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International Conference on Document Analysis and recognition

作者： Shuyan Zhao Zheru Chi Pengfei Shi Qing Wang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Centre for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Computer Science and Engineering Northwestern Polytechnical University Xi'an China

ISBN: (纸本)0769512631

Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage approach is addressed to segment unconstrained handwritten Chinese character strings. A string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. At the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. Geometric features are extracted and fuzzy decision rules learned from examples are used to evaluate the segmentation paths. By using this two-stage segmentation approach, we can achieve both good performance and efficiency in segmenting unconstrained handwritten Chinese characters.

关键词： image segmentation Character recognition pattern recognition Handwriting recognition Signal processing image processing computer science Electronic mail image recognition Skeleton

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Grouping edge points into line segments by sequential hough transformation

Grouping edge points into line segments by sequential hough ...

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15th International Conference on pattern recognition, ICPR 2000

作者： Zhang, Xiaofeng Burkhardt, Hans Pattern Recognition and Image Processing Dept. of Computer Science University of Freiburg Freiburg79110 Germany

ISBN: (纸本)0769507506

An algorithm to group edge points into digital line segments with Hough transformation is described in this paper. The edge points are mapped onto the parameter domain dis-cretked at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region, to which the edge points are supposed to be mapped, is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation, detecting peaks one by one in the parameter domain, is implemented and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both generated edges disturbed by different noise levels and real images taken from indoor environment. © 2000 IEEE.

关键词： Edge detection

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Invariant grey-scale features for 3D sensor-data

Invariant grey-scale features for 3D sensor-data

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International Conference on pattern recognition

作者： M. Schael S. Siggelkow Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiberg Germany

ISBN: (纸本)0769507506

A technique for the construction of invariant features of 3D sensor-data is proposed. Invariant grey-scale features are characteristics of grey-scale sensor-data which remain constant if the sensor-data is transformed according to the action of a transformation group. The proposed features are capable of recognizing 3D objects independent of their orientation and position, which can be used e.g. in medical image analysis. The computation of the proposed invariants needs no preprocessing like filtering, segmentation, or registration. After the introduction of the general theory for the construction of invariant features for 3D sensor-data, the paper focuses on the special case of 3D Euclidean motion which is typical for rigid 3D objects. Due to the fact that we use the function of local support the calculated invariants are also robust with respect to independent Euclidean motion, articulated objects, and even topological deformations. The complexity of the method is linear in the data-set size which may be too high for large 3D objects. Therefore approaches for the acceleration of the computation are given. First experimental results for artificial 3D objects are presented in the paper to demonstrate the invariant properties of the proposed features.

关键词： Geometry pattern recognition Biomedical imaging Robustness image processing computer science image recognition image motion analysis Lubricating oils image segmentation

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Grouping edge points into line segments by sequential Hough transformation

Grouping edge points into line segments by sequential Hough ...

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International Conference on pattern recognition

作者： Xiaofeng Zhang H. Burkhardt Chair of Pattern Recognition and Image Processing Department of Computer Science University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769507506

An algorithm to group edge points into digital line segments with Hough transformation is described. The edge points are mapped onto the parameter domain discretized at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region to which the edge points are supposed to be mapped is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation for detecting peaks one by one in the parameter domain is implemented, and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both the generated edges disturbed by different noise levels and real images taken from an indoor environment.

关键词： image segmentation image edge detection Indoor environments Face detection pattern recognition image processing computer science Noise robustness Noise level Noise measurement

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Polarization images: a geometric interpretation for shape analysis

Polarization images: a geometric interpretation for shape an...

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International Conference on pattern recognition

作者： S. Rahmann Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769507506

Presents a framework for the geometric interpretation of a single polarization image taken of specular reflecting objects. The task of recovering 3D shape information of specular objects from intensity images is a difficult if not impossible one, as no intensity based features are available. Polarization analysis provides additional features to overcome the problem. In particular the orientation of polarized light is measured, from which constraints on the object surface can be deduced. We show how to perform shape analysis from a single polarization image. The method is applied to local deformation measuring. Along with a discussion of polarization and related geometric issues, algorithms are presented and substantiated by experiments.

关键词： Shape image analysis Optical polarization Optical reflection Rough surfaces Surface roughness Surface reconstruction Performance analysis Lighting image reconstruction

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Fuzzy c-means in an MDL-framework

Fuzzy c-means in an MDL-framework

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International Conference on pattern recognition

作者： A. Selb H. Bischof A. Leonardis Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia

ISBN: (纸本)0769507506

In this paper we present a minimum description length (MDL) framework for fuzzy clustering algorithms. This framework enables us to find an optimal number of cluster centers. We applied our approach to the fuzzy c-means algorithm for which we designed a computationally efficient procedure. We report the results of our approach on a 2D clustering problem and on RGB color image segmentation.

关键词： Clustering algorithms Radial basis function networks Encoding Color image segmentation image recognition image processing Algorithm design and analysis Unsupervised learning pattern recognition

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Multiple eigenspaces by MDL

Multiple eigenspaces by MDL

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International Conference on pattern recognition

作者： A. Leonardis H. Bischof Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

ISBN: (纸本)0769507506

We propose an approach to constructing multiple eigenspaces from a set of training images based on the minimum description length (MDL) principle. The main idea is to systematically build a redundant set of eigenspaces, which are treated as hypotheses that are then subject to a selection procedure. The selection procedure, based on the MDL principle, selects the final resulting set of eigenspaces as an optimal representation of the training set. We have tested the proposed method on a number of standard image sets, and the significance of the approach with respect to the recognition rate has been clearly demonstrated.

关键词： Testing image recognition Principal component analysis Information science image analysis image reconstruction pattern recognition image processing Robustness Robust control

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Minimizing the topological structure of line images 7th

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7th Joint IAPR International Workshop on Structural and Syntactic pattern recognition, SSPR 1998 and 2nd International Workshop on Statistical Techniques in pattern recognition, SPR 1998

作者： Kropatsch, Walter G. Burge, Mark Vienna University of Technology Institute of Automation 183/2 Pattern Recognition and Image Processing Group Treitlstr.3 WienA-1040 Austria Johannes Kepler University Institute of Systems Science Computer Vision Laboratory LinzA-4040 Austria

ISBN: (纸本)3540648585

We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) steps. A MLPP graph of a line image compliments the structural information in geometric graph representations like the run graph. Using such a graph and its dual, line image analysis systems can efficiently detect topological features like loops and holes and make use of relations like containment. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Topology

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A Region-Based Representation of images in MARS

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Journal of VLSI Signal processing Systems for Signal, image, and Video Technology 1998年第1-2期20卷 137-150页

作者： Servetto, Sergio D. Rui, Yong Ramchandran, Kannan Huang, Thomas S. Beckman Inst. Adv. Sci. and Technol. Univ. Illinois at Urbana-Champaign Urbana IL 61801 United States Universidad Nacional de La Plata Argentina Univ. Illinois at Urbana-Champaign United States Comp. Res. Adv. Applications Group IBM Argentina Argentina Image Formation and Processing Group Beckman Institute UIUC United States Department of Computer Science UNLP Argentina Dept. of Elec. and Comp. Engineering UIUC United States Multimedia Commun. Res. Department Bell Laboratories Murray Hill NJ United States Info. Sciences Research Department AT and T Labs. Florham Park NJ United States Department of Computer Science UIUC United States Southeast University China Tsinghua University China University of Illinois Urbana-Champaign IL United States Image Formation and Processing Group Beckman Inst. Advance Sci. Technol. UIUC United States Vis. Technol. Grp. of Microsoft Res. Redmond WA United States City College of New York United States Columbia University United States AT and T Bell Labs. United States Ctr. for Telecommunications Research Columbia University United States Elec. and Comp. Eng. Department United States Beckman Institute Coordinated Science Laboratory IL United States IEEE Signal Processing Society United States IEEE IMDSP Technical Committee United States IEEE Transactions on Image Proc. United States National Taiwan University Taipei Taiwan Massachusetts Inst. of Technology Cambridge MA United States Department of Electrical Engineering MIT United States School of Electrical Engineering United States Lab. for Info. and Signal Processing Purdue University United States Dept. of Elec. and Comp. Engineering United States Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Inst. Adv. Sci. and Technol. United States MIT Lincoln Laboratory IBM Thomas J. Watson Research Center Rheinishes Landes Museum Bonn Germany Swiss Institutes of Technology Zurich Switzerland Swiss Institutes of Technology Lausanne S

We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propose new image coding techniques which combine a wavelet representation, embedded coding of the wavelet coefficients, and segmentation of image-domain regions in the wavelet domain. A bitstream is generated in which each image region is encoded independently of other regions, without having to explicitly store information describing the regions. Simulation results show that our proposed algorithms achieve coding performance which compares favorably, both perceptually and objectively, to that achieved using state-of-the-art image/video coding techniques while additionally providing region-based support.

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On-line fingerprint verification

On-line fingerprint verification

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13th International Conference on pattern recognition, ICPR 1996

作者： Jain, Anil Hong, Lin Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI 48824 United States

ISBN: (纸本)081867282X

We describe the design and implementation of an online fingerprint verification system which operates in two stages: (i) minutia extraction and (ii) minutia matching. An improved minutia extraction algorithm that is much faster and more accurate than our earlier algorithm has been implemented. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between input minutiae and the stored template without resorting to exhaustive search and has the ability to adaptively compensate for the nonlinear deformations and inexact pose transformations between finger prints. The system has been tested on two sets of finger print images captured with inkless scanners. The verification accuracy is found to be over 99% with a 15% reject rate. Typically, a complete fingerprint verification procedure takes, on an average, about 8 seconds on a SPARC 20 workstation. It meets the response time requirements of on-line verification with high accuracy. © 1996 IEEE.

关键词： Mathematical transformations

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