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International Conference on pattern recognition

作者： Aysylu Gabdulkhakova Walter G. Kropatsch Pattern Recognition and Image Processing group Technische Universität Wien Vienna Austria

ISBN: (纸本)9781728188089;9781728188096

In this paper the properties of the generalized conics are used to create a unified framework for generating various types of the distance fields. the main concept behind this work is a metric that measures the distance from a point to a line segment according to the definition of the ellipse. the proposed representation provides a possibility to efficiently compute the proximity, arithmetic mean of the distances and a space tessellation with regard to the given set of polygonal objects, line segments and points. In addition, the weights can be introduced for objects, their parts and combinations. this fact leads to a hierarchical representation that can be efficiently obtained using the pixel-wise operations. the practical value of the proposed ideas is demonstrated on an example of applications like skeletonization, smoothing and optimal location finding.

关键词： Measurement image segmentation Smoothing methods transforms Planning pattern recognition

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Confocal Ellipse-based Distance and Confocal Elliptical Field for polygonal shapes

Confocal Ellipse-based Distance and Confocal Elliptical Fiel...

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International Conference on pattern recognition

作者： Aysylu Gabdulkhakova Walter G. Kropatsch Pattern Recognition and Image Processing group Technische Universität Wien Vienna Austria

the paper introduces a novel confocal ellipse-based distance (CED), that is based on the properties of the confocal ellipses. this distance is used to produce a confocal elliptical field (CEF). the Euclidean Distance transform (EDt) of a single point (called seed) generates a distance field of concentric circles. the sum of two such distance fields of two distinct seed points produces a distance field of confocal ellipses. this fact enables to adapt CED and CEF to the discrete case, referred to as CED-Dt and CEF-Dt. the properties of the CEF and CEF-Dt make them useful for skeletonization, in particular for efficient removal of the spurious branches.

关键词： Shape Skeleton transforms image processing Euclidean distance two dimensional displays pattern recognition

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Document understanding of graphical content in natively digital PDF documents 12

Document understanding of graphical content in natively digi...

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2012 ACM Symposium on Document Engineering, DocEng 2012

作者： Gabdulkhakova, Aysylu Hassan, tamir Department of Computing Mathematics and Cybernetics Ufa State Aviation Technical University K. Marx str. 12 450000 Ufa Russia Pattern Recognition and Image Processing Group Technische Universität Wien Favoritenstraße 9-11 1040 Wien Austria

ISBN: (纸本)9781450311168

this paper presents an object-based method for analysing the content drawn by graphical operators in natively digital PDF documents. We propose that graphical content in a document can be classified either as structural or nonstructural and present an output model for our analysis result. Heuristic techniques are used to group the instructions into regions and determine their logical role in the document's structure. Experimental results demonstrate the effectiveness of the algorithm. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM).

关键词： Structural analysis

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Preface

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2001年 2130卷 v页

作者： Dorffner, Georg Bischof, Horst Hornik, Kurt University of Vienna Dept. of Mecidal Cybernetics and Artificial Intelligence Freyung 6/2 Vienna Austria Technical University of Vienna Institute for Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr. 9/1832 Vienna Austria Wirtschaftsuniversität Wien Institut für Statistik Augasse 2-6 Wien Austria

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PCA-Pyramids for image Compression 7

PCA-Pyramids for Image Compression

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7th International Conference on Neural Information processing Systems, NIPS 1994

作者： Bischof, Horst Hornik, Kurt Department for Pattern Recognition and Image Processing Technical University Vienna Treitlstraße 3/1832 ViennaA-1040 Austria Institut für Statistik und Wahrscheinlichkeitstheorie Technische Universität Wien Wiedner Hauptstraße 8-10/1071 ViennaA-1040 Austria

this paper presents a new method for image compression by neural networks. First, we show that we can use neural networks in a pyramidal framework, yielding the so-called PCA pyramids. then we present an image compression method based on the PCA pyramid, which is similar to the Laplace pyramid and wavelet transform. Some experimental results with real images are reported. Finally, we present a method to combine the quantization step with the learning of the PCA pyramid. © NIPS *** rights reserved.

关键词： image compression

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PCA-pyramids for image compression 94

PCA-pyramids for image compression

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Proceedings of the 8th International Conference on Neural Information processing Systems

作者： Horst Bischof Kurt Hornik Department for Pattern Recognition and Image Processing Technical University Vienna Vienna Austria Institut für Statistik und Wahrscheinlichkeitstheorie Technische Universität Wien Vienna Austria

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