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International Conference on Document Analysis and recognition

作者： S. Wachenfeld H.-U. Klein X. Jiang Computer Vision and Pattern Recognition Group Department of Computer Science University of Münster Germany

The recognition of screen-rendered text is a novel task. It is performed e.g. by translation tools which allow users to click on any text on the screen and give a translation. Also some commercial OCR programs start to address the problem of reading screenshots. Optical character recognition on screen-shot images can be very challenging due to very small and smoothed fonts. In order to build and compare recognition approaches for screen-rendered text, the availability of standard databases is a fundamental prerequisite. In this paper two freely available databases are presented, one that consists of annotated screenshot images of 28080 single characters and another holding 400 words extracted from documents plus 2 400 generated isolated words. Both databases include meta-information such as x-height, font type, style and rendering conditions. At the example of a developed recognition system, it is shown how these databases can serve for training, testing and optimization.

关键词： Text recognition Image databases Optical character recognition software System testing pattern recognition Rendering (computer graphics) Operating systems Character recognition Character generation Application software

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A ROBOTIC SYSTEM FOR PCBS INSPECTION BASED ON computer vision AND MOBILE PROBES

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IFAC Proceedings Volumes 2007年第3期40卷 171-176页

作者： J. Gómez J. Gámez A.G. González L. Nieto S. Satorres A. Sanchez System Engineering and Automation Department Jaen University Campus las Lagunillas s/n Jaén Spain.

In this paper a new robotized inspection system for PCBs is presented. Electrical and optical tests are carried out by the system, using four mobile probes where two micro CCD cameras are mounted. This new approach becomes a costless and quick setup alternative to the currently used spiked beds for those applications of prototyping developments where maximum flexibility is demanded for the inspection system. A computer vision system provides the capacity for optical inspections where visual tests, like part presence/absence or polarity, can be performed.

关键词： Robotics Automatic Testing Position Control Visual pattern recognition

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Teamwork recognition of embodied agents with hidden Markov models

Teamwork recognition of embodied agents with hidden Markov m...

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IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Linus J. Luotsinen Hans Fernlund Ladislau Boloni School of Electrical Engineering and Computer Science University of Central Florida Orlando FL USA

Recognizing and annotating the occurrence of team actions in observations of embodied agents has applications in surveillance or in training of military or sport teams. We describe the team actions through a spatio-temporal correlated pattern of movement, which can be modeled by a hidden Markov model. The hand-crafting of these models is a difficult task of knowledge engineering, even in application domains where explicit, natural language descriptions of the team actions are available. The main contribution of this paper is an approach through which the library of HMM representations can be acquired from a small number of hand annotated, representative samples of the specific movement patterns. A series of experiments, performed on a dataset describing a real-world terrestrial warfare exercise validates our method and shows good recognition accuracy even in the presence of noisy data. The speed of the recognition engine is sufficiently fast to allow real time annotation of incoming observations.

关键词： Teamwork Hidden Markov models Event detection pattern recognition computer vision Video recording Layout Video sequences Object detection Surveillance

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Perceptual Surface Roughness Classification of 3D Textures Using Support Vector Machines

Perceptual Surface Roughness Classification of 3D Textures U...

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IEEE International Workshop on Haptic, Audio and Visual Environments and Their Applications

作者： Troy L. McDaniel Sethuraman Panchanathan Center for Cognitive Ubiquitous Computing Department of Computer Science and Engineering Arizona State University Tempe AZ USA

Perceptual surface roughness classification describes how a surface's texture feels haptically in terms of perceptual categories such as smooth, rough, bumpy, etc. computer vision and pattern recognition algorithms which estimate a surface's perceptual roughness have a wide range of application areas including robotics, assistive devices, telesurgery and teleperception. In this paper, we propose a novel approach to perceptual surface roughness classification that, unlike previous approaches, is designed to handle multiple roughness categories within the same image. The steps of our approach include (1) texton extraction and classification using a multi-class, non-linear Support Vector Machine; (2) segmentation using the Iterated Conditional Modes algorithm; and (3) overall perceptual roughness classification using a Nearest Neighbor classifier. The proposed approach is evaluated using visio-haptic subjective measures of roughness on images of the 3D texture of real world objects.

关键词： Rough surfaces Surface roughness Surface texture Support vector machines Support vector machine classification computer vision pattern recognition Application software Robot vision systems Image segmentation

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A Decoupled Algorithm for vision Parameter Estimation with Application to the Trifocal Tensor

A Decoupled Algorithm for Vision Parameter Estimation with A...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Tony Scoleri Wojciech Chojnacki Michael J. Brooks Defence Science and Technology Organisation Edinburgh SA Australia School of Computer Science University of Adelaide Adelaide SA Australia

ISBN: (纸本)9781424431618;9780769530673

We consider the problem of estimating parameters of a model described by a system of equations which underlies a wide class of computer vision applications. One method to solve such a problem is the fundamental numerical scheme (FNS) previously proposed by some of the authors. In this paper, a more stable version of FNS is developed, with better convergence properties than the original version. The improvement in performance is achieved by reducing the original estimation problem to a couple of problems of lower dimension. By way of example, the new algorithm has been applied to the problem of estimating the trifocal tensor relating three views of a scene. Experiments carried out with both synthetic and real images reveal the new estimator to be more stable compared to the original FNS method, and commensurate in accuracy with the Gold Standard maximum likelihood estimator.

关键词： Parameter estimation Tensile stress computer vision Application software Maximum likelihood estimation Australia Equations Convergence Phase estimation Digital images

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Automation of Document Editing: A vision Based Approach

Automation of Document Editing: A Vision Based Approach

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International Conference on Computational Intelligence and Multimedia Applications

作者： Jyothi B. Kiranagi Bapu B. Kiranagi D.S. Guru Department of Studies in Computer Science University of Mysore Manasagangotri-Mysore Mysore India

ISBN: (纸本)9780769530505;0769530508

In this paper, a method automating the task of document editing is proposed. The methodology involves a new algorithm to recognize hand written symbols and their positions in printed document. Further, a software package is developed to automate the task of incorporating the suggested corrections (on a hard copy) into the soft copy. The package is develop using pattern recognition and image processing techniques.

关键词： Automation Image segmentation Image processing Feature extraction pattern recognition Visual BASIC Computational intelligence Application software computer science Software packages

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2007 22nd International symposium on computer and information sciences

2007 22nd International symposium on computer and informatio...

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International International Symposium on computer and Information Sciences (ISCIS)

The following topics are dealt with: machine learning; signal processing; computer graphics; computer vision; pattern recognition; security; information assurance; computer networks; P2P networks; embedded systems; system architecture; wireless sensor networks; high performance network control; high performance network management; optical networks; database management; information retrieval; document and text processing; data and software engineering; information systems applications; data management and algorithms.

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A Universal Method for Hierarchical Object recognition based on Low-Power vision Sensors

A Universal Method for Hierarchical Object Recognition based...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Felix Lustenberger David Beyeler Edo Franzi Peter Seitz Thierry Zamofing Image Sensing Photonics and Microelectronics Divisions Zurich Center CSEM Zurich Switzerland

A universal software framework for hierarchical object recognition has been devised based on V. B. Mountcastle's observation (Mountcastle, 1978) that the human cortex consists of the same basic functionality which is used to subdivide the complex computations into elementary matching tasks, independently whether auditory, visual, olfactory, haptic or any other sensory information is presented at the input. Combined with a unique vision sensor system that is capable to directly extract contrast magnitude and direction, a powerful combination of hardware and software for real-time pattern-recognition tasks at very low power-consumption levels is presented

关键词： Object recognition computer vision Application software Image sensors Optoelectronic and photonic sensors Microelectronics Humans Optical computing Olfactory Haptic interfaces

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Incorporating User Provided Constraints into Document Clustering

Incorporating User Provided Constraints into Document Cluste...

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IEEE International Conference on Data Mining (ICDM)

作者： Yanhua Chen Manjeet Rege Ming Dong Jing Hua Department of Computer Science Machine Vision and Pattern Recognition Laboratory Detroit MI USA Department of Computer Science Graphics and Imaging Laboratory Detroit MI USA

Document clustering without any prior knowledge or background information is a challenging problem. In this paper, we propose SS-NMF: a semi-supervised non- negative matrix factorization framework for document clustering. In SS-NMF, users are able to provide supervision for document clustering in terms of pairwise constraints on a few documents specifying whether they "must" or "cannot" be clustered together. Through an iterative algorithm, we perform symmetric tri-factorization of the document- document similarity matrix to infer the document clusters. Theoretically, we show that SS-NMF provides a general framework for semi-supervised clustering and that existing approaches can be considered as special cases of SS-NMF. Through extensive experiments conducted on publicly available data sets, we demonstrate the superior performance of SS-NMF for clustering documents.

关键词： Iterative algorithms Clustering algorithms Symmetric matrices Data mining Databases Clustering methods Couplings Machine vision pattern recognition computer graphics

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Advances in Discrete Tomography and Its Applications 1

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丛书名： Applied and Numerical Harmonic Analysis

2007年

作者： Gabor T. Herman Attila Kuba

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