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Automated stroke ending analysis for drawing tool classification

Automated stroke ending analysis for drawing tool classifica...

引用

International Conference on pattern recognition

作者： Maria C. Vill Robert Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria

ISBN: (纸本)9781424421749

This paper proposes a drawing tool recognition method based on features calculated from the shape of stroke endings. The application for this method is to help art historians to identify the drawing tool used for a drawing. Since the style of a drawing depends on the drawing tool used, drawing tool recognition is an important step toward a style analysis. A dominant feature of a drawn stroke is its ending. Several features regarding curvature, proportions etc. are calculated out of the shape of the endings. These features are then used to classify stroke endings with a SVM classifier.

关键词： Skeleton Shape pattern recognition Art Painting image segmentation Gray-scale Joining processes image analysis pattern analysis

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Ancient document analysis based on text line extraction

Ancient document analysis based on text line extraction

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International Conference on pattern recognition

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

ISBN: (纸本)9781424421749

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our cultural heritage and for automated document processing libraries and national archives have started digitizing historical documents.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.

关键词： Text analysis Degradation Algorithm design and analysis image segmentation image analysis Spatiotemporal phenomena Information analysis Data mining Software libraries Clustering algorithms

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Contrast Enhancement in Multispectral images by Emphasizing Text Regions

Contrast Enhancement in Multispectral Images by Emphasizing ...

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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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Registration of multi-spectral manuscript images

Registration of multi-spectral manuscript images

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8th International Symposium on Virtual Reality, Archaeology, and Intelligent Cultural Heritage, VAST 2007

作者： Diem, M. Lettner, M. Sablatnig, R. Pattern Recognition and Image Processing Group Institute for Computer Aided Automation Vienna University of Technology Austria

ISBN: (纸本)9783905674019

Two medieval Slavonic manuscripts are recorded, investigated and analyzed by philologists in collaboration with computer scientists. The aim of the project is to develop algorithms that support the philologists by automatically deriving the description and restoration of the scripts. The parchment partially contains two scripts, where the first script was erased. In order to enhance the erased script, the manuscript pages are imaged in seven bands between 330 and 1000 nm. A registration, aligning the resultant images, is necessary so that further image processing algorithms can 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 preliminary results are presented in this paper. © The Eurographics Association 2007.

关键词： image enhancement

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Propagation of uncertainty in landmark based self-localization of autonomous mobile robots

Propagation of uncertainty in landmark based self-localizati...

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10th IAPR Conference on Machine Vision Applications, MVA 2007

作者： Bais, Abdul Sablatnig, Robert Khawaja, Yahya M. Novak, Gregor Institute of Computer Technology Vienna University of Technology Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation ViennaUniversity of Technology Vienna Austria Department of Electrical Engineering NWFP University of Engineering and Technology Peshawar Pakistan

ISBN: (纸本)9784901122078

This paper presents uncertainty propagation in landmark based position estimation methods. Analysis of two methods has been carried out where robot position is estimated by detecting one or two globally distinct features using a pivoted stereo vision system. We make a basic assumption about error in estimating point features in camera images and propagate it into robot position estimate using first order approximation of non-linear functions. Simulation results illustrate the performance of the method.

关键词： Stereo image processing

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Ancient coins & ceramics - 3d and 2d documentation for preservation and retrieval of lost heritage 2

Ancient coins & ceramics - 3d and 2d documentation for prese...

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2nd ISPRS International Workshop on Virtual Reconstruction and Visualization of Complex Architectures, 3D-ARCH 2007

作者： Mara, Hubert Kampel, Martin Niccolucci, Franco Sablatnig, Robert PIN - Servizi Didattici e Scientifici Universit di Firenze VAST-Laboratory Piazza Ciardi 25 Prato59100 Italy Vienna University of Technology Institute for Computer Aided Automation Pattern Recognition Image Processing Group Favoritenstrasse 9/183-2 Vienna1040 Austria

Motivated by the requirements of archaeologists we are developing an automated system for acquisition, documentation and management of daily finds of excavations. These daily finds can be separated into large objects like remainders of architecture and small objects of ancient daily life - like ceramics and coins. Ceramics especially are found in numbers of tens of thousands on virtually every excavation, because ceramics have been in use for thousands of years. Until the present day these finds are documented by manual drawings. There is a similar situation in the case of coins, where manual drawings are often used to abstract them from photographs. Therefore we propose an automated acquisition and documentation system based on digital cameras and structured light for small findings. For ceramics we provide further processing to estimate horizontal cross-sections (profile-lines) for printed documentation, as it is done by manual drawing. For this a proper orientation of the acquired 3D-model is required and automatically estimated based on the assumption that ceramics were made on rotational plates (wheels). We are aware that ceramics might not always have been manufactured on rotational plates, because the wheel was not invented everywhere as for the example in the Americas. Even though ceramics from such areas appear to be rotational symmetric, we developed a method based on shape and symmetry analysis to determine the manufacturing techniques of ceramics. This helps to answer another archaeological question regarding the technological advance of an ancient culture. Results for accuracy and performance are shown on real data from recent interdisciplinary projects together with archaeologists from Austria, Germany, Israel and Peru. Furthermore we present preliminary results of the integration of coin classification in our documentation system. Additionally we are currently adapting the London Charter to ensure the intellectual integrity, reliability, transparency,

关键词： Excavation

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On ancient coin classification

On ancient coin classification

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8th International Symposium on Virtual Reality, Archaeology, and Intelligent Cultural Heritage, VAST 2007

作者： Zaharieva, M. Huber-Mörk, R. Nölle, M. Kampel, M. TU Vienna Institute for Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr. 9/183-2 A-1040 Vienna Austria ARC Seibersdorf Research GmbH Smart Systems Division High Performance Image Processing A-2444 Seibersdorf Austria ARC Seibersdorf Research GmbH Smart Systems Division Quantum Technologies A-2444 Seibersdorf Austria

ISBN: (纸本)9783905674019

Illegal trade and theft of coins appears to be a major part of the illegal antiques market. image based recognition of coins could substantially contribute to fight against it. Central component in the permanent identification and traceability of coins is the underlying classification and identification technology. The first step of a computer aided system is the segmentation of the coin in the image. Next, a feature extraction process measures the coin in order to describe the coin unambiguously. In this paper, we focus on the segmentation task, followed by a comparison of features relevant for coin classification. Results of the algorithms implemented are presented for an image database of ancient coins. © The Eurographics Association 2007.

关键词： image segmentation

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Sparse MRF appearance models for fast anatomical structure localisation

Sparse MRF appearance models for fast anatomical structure l...

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2007 18th British Machine Vision Conference, BMVC 2007

作者： Donner, René Mičušsík, Branislav Langs, Georg Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria GALEN Group Laboratoire de Mathématiques Appliquées Aux Systèmes Ecole Centrale de Paris France

ISBN: (纸本)1901725340

image segmentation methods like active shape models, active appearance models or snakes require an initialisation that guarantees a considerable overlap with the object to be segmented. In this paper we present an approach that localises anatomical structures in a global manner by means of Markov Random Fields (MRF). It does not need initialisation, but finds the most plausible match of the query structure in the image. It provides for precise, reliable and fast detection of the structure and can serve as initialisation for more detailed segmentation steps. Sparse MRF Appearance Models (SAMs) encode a priori information about the geometric configurations of interest points, local features at these points and local features along the edges of adjacent points. This information is used to formulate a Markov Random Field and the mapping of the modeled object (e.g. a sequence of vertebrae) to the query image interest points is performed by the MAX-SUM algorithm. The local image information is captured by novel symmetry-based interest points and local descriptors derived from Gradient Vector Flow. Experimental results are reported for two data-sets showing the applicability to complex medical data.

关键词： image segmentation

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Multi-label image segmentation via max-sum solver

Multi-label image segmentation via max-sum solver

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Conference on computer Vision and pattern recognition (CVPR)

作者： Banislav Micusik Tomas Pajdla Pattern Recognition and Image Processing Group Inst. of Computer Aided Automation University of Technology Vienna Austria Center for Machine Perception Dpt. of Cybernetics Czech Technical University Czech Republic

We formulate single-image multi-label segmentation into regions coherent in texture and color as a MAX-SUM problem for which efficient linear programming based solvers have recently appeared. By handling more than two labels, we go beyond widespread binary segmentation methods, e.g., MIN-CUT or normalized cut based approaches. We show that the MAX-SUM solver is a very powerful tool for obtaining the MAP estimate of a Markov random field (MRF). We build the MRF on superpixels to speed up the segmentation while preserving color and texture. We propose new quality functions for setting the MRF, exploiting priors from small representative image seeds, provided either manually or automatically. We show that the proposed automatic segmentation method outperforms previous techniques in terms of the global consistency error evaluated on the Berkeley segmentation database.

关键词： image segmentation image databases Belief propagation pattern recognition image processing automation Cybernetics Color Linear programming Markov random fields

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Local Structure Detection with Orientation-invariant Radial Configuration

Local Structure Detection with Orientation-invariant Radial ...

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Conference on computer Vision and pattern recognition (CVPR)

作者： Lech Szumilas Rene Donner Georg Langs Allan Hanbury Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

Local image descriptors have proved themselves as useful tools for many computer vision tasks such as matching points between multiple images of a scene and object recognition. Current descriptors, such as SIFT, are designed to match image features with unique local neighborhoods. However, the interest point detectors used with SIFT often fail to select perceptible local structures in the image, and the SIFT descriptor does not directly encode the local neighborhood shape. In this paper we propose a symmetry based interest point detector and radial local structure descriptor which consistently captures the majority of basic local image structures and provides a geometrical description of the structure boundaries. This approach concentrates on the extraction of shape properties in image patches, which are an intuitive way to represent local appearance for matching and classification. We explore the specificity and sensitivity of this local descriptor in the context of classification of natural patterns. The implications of the performance comparison with standard approaches like SIFT are discussed.

关键词： Detectors Shape computer vision Layout Object recognition

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