optical-character-recognition

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Optical Character Recognition

Author : Stephen V. Rice
ISBN : 9781461550211
Genre : Computers
File Size : 78. 22 MB
Format : PDF
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Optical character recognition (OCR) is the most prominent and successful example of pattern recognition to date. There are thousands of research papers and dozens of OCR products. Optical Character Rcognition: An Illustrated Guide to the Frontier offers a perspective on the performance of current OCR systems by illustrating and explaining actual OCR errors. The pictures and analysis provide insight into the strengths and weaknesses of current OCR systems, and a road map to future progress. Optical Character Recognition: An Illustrated Guide to the Frontier will pique the interest of users and developers of OCR products and desktop scanners, as well as teachers and students of pattern recognition, artificial intelligence, and information retrieval. The first chapter compares the character recognition abilities of humans and computers. The next four chapters present 280 illustrated examples of recognition errors, in a taxonomy consisting of Imaging Defects, Similar Symbols, Punctuation, and Typography. These examples were drawn from large-scale tests conducted by the authors. The final chapter discusses possible approaches for improving the accuracy of today's systems, and is followed by an annotated bibliography. Optical Character Recognition: An Illustrated Guide to the Frontier is suitable as a secondary text for a graduate level course on pattern recognition, artificial intelligence, and information retrieval, and as a reference for researchers and practitioners in industry.

The History Of Ocr Optical Character Recognition

Author : Herbert F. Schantz
ISBN : UOM:39015006062981
Genre : Optical character recognition devices
File Size : 26. 58 MB
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Optical Character Recognition

Author : Shunji Mori
ISBN : 0471308196
Genre : Technology & Engineering
File Size : 58. 94 MB
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As optical character recognition (OCR) begins to find applications ranging from store checkout scanners to money-changing machines and postal system automation, it has become one of the most dynamic areas in information science today. Yet few volumes explore this data-oriented process without relying heavily on mathematical background reading. Now, Shunji Mori, Hirobumi Nishida, and Hiromitsu Yamada, among the field's most respected researchers since its inception, present this self-contained, clearly written guidebook to OCR--the first comprehensive treatment of the preprocessing, feature-extraction, and systematic description-matching stages of the OCR process. Including a wealth of original research material available here for the first time, this book is both an ideal professional reference source and an excellent entry point for course work in the subject. Key features of Optical Character Recognition: * Theoretical framework based on functional analysis--not previously available in a detailed, English-language version * Extensive explanation of preprocessing theory, including blurring and sampling, normalization, thinning, and binary and gray-scale morphology * Intensive section on feature extraction, exploring linear methods, structure analysis, and algebraic description * Original work on systematic shape description as a prerequisite to matching * Original material on elastic matching, including image recognition of characters and objects * Requires only the standard undergraduate requisites of algebra, linear algebra, and advanced calculus

Optical Character Recognition Character Sets

Author : United States. National Bureau of Standards
ISBN : UIUC:30112018531092
Genre : Optical character recognition devices
File Size : 33. 77 MB
Format : PDF, Kindle
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Optical Character Recognition Ocr Dot Matrix Character Sets For Ocr Ma

Author : United States. National Bureau of Standards
ISBN : UIUC:30112101564620
Genre : Electronic data processing
File Size : 48. 75 MB
Format : PDF
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Guideline For Optical Character Recognition Forms

Author : United States. National Bureau of Standards
ISBN : UIUC:30112105105156
Genre : Government publications
File Size : 73. 16 MB
Format : PDF
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Optical Character Recognition

Author : Auerbach Info, inc
ISBN : PSU:000002369921
Genre : Optical character recognition devices
File Size : 52. 8 MB
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Optical Character Recognition And The Years Ahead

Author : International Business Forms Industries
ISBN : STANFORD:36105031359743
Genre : Optical character recognition
File Size : 67. 22 MB
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Handbook Of Character Recognition And Document Image Analysis

Author : Horst Bunke
ISBN : 981022270X
Genre : Computers
File Size : 76. 59 MB
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Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.

Optical Character Recognition A Complete Guide 2020 Edition

Author : Gerardus Blokdyk
ISBN : 1867333201
Genre :
File Size : 82. 43 MB
Format : PDF, ePub
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How to open an image file for editing? Do you have efforts underway to change the position descriptions/level/series for the scanner operators? What is/are the grade level and pay series for the description(s) provided? Should it be character based or word based? Why do you use your own Optical Character Recognition (OCR) Engine? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Optical Character Recognition investments work better. This Optical Character Recognition All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Optical Character Recognition Self-Assessment. Featuring 962 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Optical Character Recognition improvements can be made. In using the questions you will be better able to: - diagnose Optical Character Recognition projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Optical Character Recognition and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Optical Character Recognition Scorecard, you will develop a clear picture of which Optical Character Recognition areas need attention. Your purchase includes access details to the Optical Character Recognition self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Optical Character Recognition Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Guideline For Optical Character Recognition Ocr Print Quality

Author : United States. National Bureau of Standards
ISBN : UIUC:30112104151128
Genre : Optical character recognition devices
File Size : 66. 79 MB
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The First Census Optical Character Recognition System Conference

Author : R. Allen Wilkinson
ISBN : UOM:35128001993748
Genre : Optical character recognition devices
File Size : 43. 97 MB
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An Optical Character Recognition Research And Demonstration Project

Author : Los Angeles County Public Library
ISBN : UOM:39015028170218
Genre : Computers
File Size : 53. 58 MB
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Optical Character Recognition In The Historical Discipline

Author : Netherlands Historical Data Archive
ISBN : UOM:39015032533468
Genre : History
File Size : 88. 30 MB
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Autonomous Repair Of Optical Character Recognition Data Through Simple Voting And Multi Dimensional Indexing Techniques

Author : Chris Sprague
ISBN : OCLC:1198603957
Genre :
File Size : 72. 30 MB
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The three major optical character recognition (OCR) engines (ExperVision, Scansoft OCR, and Abby OCR) in use today are all capable of recognizing text at near perfect percentages. The remaining errors however have proven very difficult to identify within a single engine. Recent research has shown that a comparison between the errors of the three engines proved to have very little correlation, and thus, when used in conjunction, may be useful to increase accuracy of the final result. This document discusses the implementation and results of a simple voting system designed to prove the hypothesis and show a statistical improvement in overall accuracy. Additional aspects of implementing an improved OCR scheme such as dealing with multiple engine data output alignment and recognizing application specific solutions are also addressed in this research. Although voting systems are currently in use by many major OCR engine developers, this research focuses on the addition of a collaborative system which is able to utilize the various positive aspects of multiple engines while also addressing the immediate need for practical industry applications such as litigation and forms processing. Doculex TM, a major developer and leader in the document imaging industry, has provided the funding for this research.

Real Time Optical Correlator For Optical Character Recognition

Author : James Kim-Tzong Eu
ISBN : UCSD:31822023025083
Genre : Optical character recognition
File Size : 26. 60 MB
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Optical Character Recognition Ocr Inks

Author : United States. National Bureau of Standards
ISBN : UIUC:30112104151169
Genre : Ink
File Size : 66. 12 MB
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Optimisation Based Optical Character Recognition For Historical M?ori Land Court Documents

Author : Jonathan Symons
ISBN : OCLC:1141869307
Genre : Algorithms
File Size : 49. 35 MB
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We are at risk of losing a connection to our past if we don’t convert old historical documents into a searchable, electronic form. There are thousands of documents in the M ̄aori Land Court that have been scanned but are not fully utilized because the documents aren’t stored in text format that people can search through. This research investigates the use of analytical and optimisation methodologies to enable the conversion of two scanned historical M ̄aori Land Court documents for the Parininihi ki Waitotara Incorporation into electronic text. The documents examined were degraded, with rips, tears, bends, wrinkles, fading, and smudging. Some of the documents also appear to be a scan of a printed out scanned image, making them harder to convert. Professional recognition software was tested to no avail.This thesis implemented algorithms specific to the documents. Minimal pre-processing was conducted on the original image. Instead, the majority of the image issues are addressed in the recognition stage. To segment the characters, we test several algorithms. Four different blob finding techniques were chosen to segment the characters, including the Laplacian of Gaussian (LoG), Difference of Gaussian (DoG), Determinant of Hessian (DoH), and MSER. The MSER algorithm worked the best of the four implemented. We also test the usage of character contours to segment the characters. As an alternative to heuristics and neural networks, optimisation techniques are used to locate the individual characters. This is accomplished with a dynamic program, which uses the structure of the typewriter to break the page down into the different lines of text and individual columns of characters. Template matching heuristics are used to recognize the located characters. While the results are significantly better than from the generic state of the art professional packages, there is still room for improvement with a character recognition rate of 76% and 58%. To improve this rate, we apply a dictionary matching algorithm to ensure that the string of recognized characters is an actual word or number sequence. This gives an accuracy of 86% and 67%.

Optical Character Recognition And Document Segmentation

Author : Conrad Sabourin
ISBN : OCLC:1150928444
Genre : Computational linguistics
File Size : 57. 94 MB
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Optical Character Recognition; Proceedings

Author : George L. Fischer
ISBN : WISC:89037551884
Genre : Optical character recognition
File Size : 76. 8 MB
Format : PDF, Docs
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