By Mohamed Cheriet, Nawwaf Kharma, Cheng-Lin Liu, Ching Suen
"Much of trend attractiveness concept and perform, together with equipment reminiscent of help Vector Machines, has emerged in an try to resolve the nature reputation challenge. This booklet is written by way of very recognized teachers who've labored within the box for a few years and feature made major and lasting contributions. The publication will doubtless be of worth to scholars and practitioners."
-Sargur N. Srihari, SUNY extraordinary Professor, division of computing device technological know-how and Engineering, and Director, heart of Excellence for record research and popularity (CEDAR), collage at Buffalo, The country college of recent York
"The disciplines of optical personality popularity and rfile snapshot research have a background of greater than 40 years. within the final decade, the significance and recognition of those components have grown vastly. strangely, despite the fact that, the sector isn't good coated through any textbook. This e-book has been written via widespread leaders within the box. It comprises all very important themes in optical personality attractiveness and rfile research, and is written in a really coherent and complete kind. This publication satisfies an pressing want. it's a quantity the group has been waiting for for a very long time, and that i can enthusiastically suggest it to each person operating within the area."
-Horst Bunke, Professor, Institute of desktop technology and utilized arithmetic (IAM), collage of Bern, Switzerland
In personality attractiveness structures, the authors offer practitioners and scholars with the elemental rules and cutting-edge computational tools of examining revealed texts and handwritten fabrics. the data awarded is comparable to the levels of a working laptop or computer acceptance procedure, supporting readers grasp the idea and newest methodologies utilized in personality acceptance in a significant way.
This booklet covers:
views at the historical past, functions, and evolution of Optical personality attractiveness (OCR)
the main prevalent pre-processing suggestions, in addition to tools for extracting personality contours and skeletons
comparing extracted positive factors, either structural and statistical
glossy class equipment which are winning in personality attractiveness, together with statistical equipment, man made Neural Networks (ANN), help Vector Machines (SVM), structural equipment, and multi-classifier methods
an summary of note and string reputation tools and techniques
Case reports that illustrate useful functions, with descriptions of the equipment and theories in the back of the experimental results
each one bankruptcy includes significant steps and tips to deal with the projects defined at-hand. Researchers and graduate scholars in laptop technology and engineering will locate this booklet helpful for designing a concrete procedure in OCR expertise, whereas practitioners will depend upon it as a helpful source for the most recent advances and sleek applied sciences that are not coated in different places in one book.Content:
Chapter 1 creation: personality popularity, Evolution, and improvement (pages 1–4):
Chapter 2 instruments for photograph Preprocessing (pages 5–53):
Chapter three characteristic Extraction, choice, and production (pages 54–128):
Chapter four development category equipment (pages 129–203):
Chapter five note and String acceptance (pages 204–262):
Chapter 6 Case experiences (pages 263–320):
Read or Download Character Recognition Systems: A Guide for Students and Practioners PDF
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Extra resources for Character Recognition Systems: A Guide for Students and Practioners
Form identification: for an input form image, identify the most suitable form model from a database. • Layout analysis: understand the structure of forms and the semantic meaning of the information in tables or forms. • Data extraction: extract pertinent data from respective fields and preprocess the data to remove noise and enhance the data. • Character recognition: convert the gray or binary images that contain textual information to electronic representation of characters that facilitate postprocessing including data validation and syntax analysis.
Skew can even be intentionally designed to emphasize important details in a document. However, this effect is unintentional in many real cases, and it should be eliminated because it dramatically reduces the accuracy of the subsequent processes, such as page segmentation/classification and optical character recognition (OCR). Therefore, skew detection is one of the primary tasks to be solved in document image analysis systems, and it is necessary for aligning a document image before further processing.
Bunke and P. S. P. Wang. Handbook of Character Recognition and Document Image Analysis. World Scientific Publishing, Singapore, 1997. 2. S. Mori, H. Nishida, and H. Yamada. Optical Character Recognition, Wiley Interscience, New Jersey, 1999. 3. Optical Character Recognition and the Years Ahead. The Business Press, Elmhurst, IL, 1969. 4. Pas d’auteur. Auerbach on Optical Character Recognition. , Princeton, 1971. 5. S. V. Rice, G. Nagy, and T. A. Nartker. Optical Character Recognition: An Illustrated Guide to the Frontier.