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检索条件"机构=Pattern Recognition and Image Analysis Laboratory"

共 23 条记录，以下是11-20 订阅

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Restoration of Arbitrarily Warped Historical Document images Using Flow Lines

Restoration of Arbitrarily Warped Historical Document Images...

引用

International Conference on Document analysis and recognition

作者： Maryam Rahnemoonfar Apostolos Antonacopoulos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford UK

ISBN: (纸本)9781457713507

Historical documents frequently suffer from arbitrary geometric distortions (warping and folds) due to storage conditions, use and to, some extent, the printing process of the time. In addition, page curl can be prominent due to the scanning technique used. Such distortions adversely affect OCR and print-on-demand quality. Previous approaches to geometric restoration either focus only on the correction of page curl or require supplementary information obtained by additional scanning hardware - not practical for existing scans. This paper presents a new approach to detect and restore arbitrary warping and folds, in addition to page curl. Warped text lines and the smooth deformation between them are precisely modelled as primary and secondary flow lines that are then restored to their original linear shape. Preliminary, but representative, experimental results, in comparison to a leading page curl removal method and an industry-standard commercial system, demonstrate the effectiveness of the proposed method.

关键词： Text analysis

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Historical Document Layout analysis Competition

Historical Document Layout Analysis Competition

引用

International Conference on Document analysis and recognition

作者： A. Antonacopoulos C. Clausner C. Papadopoulos S. Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Greater Manchester UK

ISBN: (纸本)9781457713507

This paper presents an objective comparative evaluation of layout analysis methods for scanned historical documents. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2011 and the International Workshop on Historical Document Imaging and Processing (HIP2011), presenting the results of the evaluation of four submitted methods. A commercial state-of-the-art system is also evaluated for comparison. Two scenarios are reported in this paper, one evaluating the ability of methods to accurately segment regions and the other evaluating the whole pipeline of segmentation and region classification (with a text extraction goal). The results indicate that there is a convergence to a certain methodology with some variations in the approach. However, there is still a considerable need to develop robust methods that deal with the idiosyncrasies of historical documents.

关键词： Layout Particle separators Text analysis Performance evaluation Libraries image segmentation Corporate acquisitions

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The PAGE (Page analysis and Ground-Truth Elements) Format Framework

The PAGE (Page Analysis and Ground-Truth Elements) Format Fr...

引用

International Conference on pattern recognition

作者： Stefan Pletschacher Apostolos Antonacopoulos Pattern Recognition and Image Analysis Research Laboratory School of Computing Science and Engineering University of Sanford UK

There is a plethora of established and proposed document representation formats but none that can adequately support individual stages within an entire sequence of document image analysis methods (from document image enhancement to layout analysis to OCR) and their evaluation. This paper describes PAGE, a new XML-based page image representation framework that records information on image characteristics (image borders, geometric distortions and corresponding corrections, binarisation etc.) in addition to layout structure and page content. The suitability of the framework to the evaluation of entire workflows as well as individual stages has been extensively validated by using it in high-profile applications such as in public contemporary and historical ground-truthed datasets and in the ICDAR Page Segmentation competition series.

关键词： Layout Text analysis Joining processes Performance evaluation XML Pipelines Optical character recognition software

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Evaluating deformation patterns of the thoracic aorta in gated CTA sequences

Evaluating deformation patterns of the thoracic aorta in gat...

引用

IEEE International Symposium on Biomedical Imaging

作者： Ernst Schwartz Roman Gottardi Johannes Holfeld Christian Loewe Martin Czerny Georg Langs Computational Image Analysis and Radiology Lab (CIR) Medical University of Vienna Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria Division of Cardiothoracic Surgery Department of Surgery Medical University of Vienna Austria Division of Interventional Radiology Department of Radiology Medical University of Vienna Austria Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology USA

ISBN: (纸本)9781424441259;9781424441266

Cardiovascular interventions in the region of the aortic isthmus such as stent-grafting and vessel transposition introduce substantial changes in the deformation properties of the affected vessels. The changes play a fundamental role in the long-term prognosis for any such treatment, but are only poorly understood to date. We explore a fully automated method to quantify the deformation patterns of the thoracic aorta in gated computed tomography sequences. The aorta is segmented by a level set approach that accurately identifies the vessel lumen in each frame of the sequence. Consequently, landmarks on the vessel wall in each frame are registered using a probabilistic method. This allows for the measurement of global and local deformation properties. We evaluate our method on synthetic datasets and report first results of its application on real world data.

关键词： Biomedical imaging image segmentation Radiology Cardiology Surgery Computed tomography Level set Electrocardiography Pathology Deformable models

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ICDAR 2009 Page Segmentation Competition

ICDAR 2009 Page Segmentation Competition

引用

International Conference on Document analysis and recognition

作者： Apostolos Antonacopoulos Stefan Pletschacher David Bridson Christos Papadopoulos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Sanford Manchester UK

This paper presents an objective comparative evaluation of layout analysis methods in realistic circumstances. It describes the Page Segmentation competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2009 and presents the results of the evaluation of four submitted methods. Two state-of-the art methods are also compared as well as the three methods from the ICDA2007 Page Segmentation competition. The results indicate that although methods continue to mature, there is still a considerable need to develop robust methods that deal with everyday documents.

关键词： image segmentation image analysis Text analysis pattern analysis pattern recognition image recognition Art Robustness image enhancement Pixel

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A Self-Adaptive Method for Extraction of Document-Specific Alphabets

A Self-Adaptive Method for Extraction of Document-Specific A...

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International Conference on Document analysis and recognition

作者： Stefan Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Sanford Greater Manchester UK

ISBN: (纸本)9781424445004

recognition and encoding of digitized historical documents is still a challenging and difficult task. A major problem is the occurrence of unknown glyphs and symbols which might not even exist in modern alphabets. Current pre-trained OCR-methods hardly deliver usable results for such documents. This paper describes an alternative approach and framework for handling printed historical documents without restrictions on the contained alphabets or fonts. The basic idea is to derive all information required for encoding directly from the document itself. This is achieved by extracting a document-specific prototype alphabet of locatable glyphs. Core of the system is a customized clustering method which adapts automatically to new documents by ascertaining appropriate threshold parameters based on the special characteristics of glyphs. This way, the system is able to run without manual interventions and can be integrated into automated mass digitization workflows.

关键词： Prototypes Optical character recognition software pattern recognition Data mining image analysis image recognition Document handling Encoding Dictionaries Character recognition

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A Realistic Dataset for Performance Evaluation of Document Layout analysis

A Realistic Dataset for Performance Evaluation of Document L...

引用

International Conference on Document analysis and recognition

作者： Apostolos Antonacopoulos David Bridson Christos Papadopoulos Stefan Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Sanford Greater Manchester UK

ISBN: (纸本)9781424445004

There is a significant need for a realistic dataset on which to evaluate layout analysis methods and examine their performance in detail. This paper presents a new dataset (and the methodology used to create it) based on a wide range of contemporary documents. Strong emphasis is placed on comprehensive and detailed representation of both complex and simple layouts, and on colour originals. In-depth information is recorded both at the page and region level. Ground truth is efficiently created using a new semi-automated tool and stored in a new comprehensive XML representation, the PAGE format. The dataset can be browsed and searched via a Web-based front end to the underlying database and suitable subsets (relevant to specific evaluation goals) can be selected and downloaded.

关键词： Text analysis Performance analysis image analysis pattern analysis pattern recognition image color analysis image recognition Data engineering XML Databases

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A New Framework for recognition of Heavily Degraded Characters in Historical Typewritten Documents Based on Semi-Supervised Clustering

A New Framework for Recognition of Heavily Degraded Characte...

引用

International Conference on Document analysis and recognition

作者： Stefan Pletschacher Jianying Hu Apostolos Antonacopoulos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Sanford Greater Manchester UK IBM Thomas J. Watson Research Center Yorktown Heights NY USA

This paper presents a new semi-supervised clustering framework to the recognition of heavily degraded characters in historical typewritten documents, where off-the-shelf OCR typically fails. The constraints are generated using typographical (collection-independent) domain knowledge and are used to guide both sample (glyph set) partitioning and metric learning. Experimental results using simple features provide encouraging evidence that this approach can lead to significantly improved clustering results compared to simple K-means clustering, as well as to clustering using a state-of-the art OCR engine.

关键词： Character recognition Degradation Optical character recognition software pattern recognition image recognition Text analysis Engines image analysis pattern analysis image texture analysis

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Exploring Bayesian networks for automated breast cancer detection

Exploring Bayesian networks for automated breast cancer dete...

引用

IEEE Southeastcon

作者： Jyotirmay Gadewadikar Ognjen Kuljaca Kwabena Agyepong Erol Sarigul Yufeng Zheng Ping Zhang The Sensors and Automation Laboratory Systems Research Institute Alcorn State University USA Vision Research Laboratory Systems Research Institute Alcorn State University USA Pattern Recognition and Image Analysis Laboratory Systems Research Institute Alcorn State University USA Systems Research Institute Alcorn State University USA

This paper gives an introduction to the Bayesian networks for the exploration of implementing a Bayesian belief network for an automated breast cancer detection support tool. It is intuitive that Bayesian networks can be employed as one viable option for computer-aided detection by representing the relationships between diagnoses, physical findings, laboratory test results, and imaging study findings. This paper brings important entities such as Radiologists, image Processing Scientists, Data Base Specialists and Applied Mathematicians on a common platform. A brief background concerning causal networks, probability theory and Bayesian networks is given. Available computational tools and platforms are described. Steps towards building a Bayesian Belief Network Implementation are introduced.

关键词： Bayesian methods Breast cancer Cancer detection Laboratories image sensors Sensor systems Automation image processing Shape Lesions

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Page Segmentation Competition

Page Segmentation Competition

引用

International Conference on Document analysis and recognition

作者： A. Antonacopoulos B. Gatos D. Bridson Pattern Recognition and Image Analysis (PRImA) Research Lab School of Computing Science and Engineering University of Sanford Manchester UK Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research Demokritos Athens Greece

This paper continues the authors' attempt to address the need for objective comparative evaluation of layout analysis methods in realistic circumstances. It describes the Page Segmentation Competition (modus operandi, dataset and evaluation criteria) held in the context of ICDAR2007 and presents the results of the evaluation of three candidate methods. The main objective of the competition was to compare the performance of such methods using scanned documents from commonly-occurring publications. The results indicate that although methods continue to mature, there is still a considerable need to develop robust methods that deal with everyday documents.

关键词： image analysis Performance analysis image segmentation Text analysis Optical character recognition software Information analysis pattern recognition Telecommunication computing Computational intelligence Informatics

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