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Automatic line segmentation in late medieval Latin manuscriptsRenet, Nicolas P. 21 July 2012 (has links)
This thesis describes a new line segmentation method that is optimized
for medieval manuscripts. Using a thinned version of the binarized document
image, the segmentation algorithm extracts two types of salient features
from the handwritten patterns: nodes, whose distribution allows for
the detection of line axes; segments, which are labeled according to the
nodes they connect. This method obtains very good results on manuscripts
that are usually considered hard to segment because of the numerous overlapping
and touching lines. By contrast with many existing segmentation
algorithms, this method does not rely on user-entered parameters and is not
overly sensitive to the quality of the preprocessing treatments. Although
more work is required to make it resistant to fluctuating lines, this line separation
technique can already handle a large set of medieval documents and
provides a useful input to a character segmentation program. / Line segmentation techniques in off-line handwriting recognition -- Line segmentation with the profile method -- Feature-based line segmentation -- Tests and conclusions. / Department of Computer Science
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Optical character recognition : an approach using self- adjusting segmentation of a matrixKirkpatrick, Michael Gorden January 1997 (has links)
The problem of optical pattern recognition is a broad one. It ranges from identifying shapes in aerial photographs to recognizing letters in hand or machine printed words. This thesis examines many of the issues relating to pattern recognition and, specifically, those pertaining to the optical recognition of characters. It discusses several approaches to various parts of the problem as an illustration of the variety of methods of attack. Some of the particular strengths and weaknesses of those approaches are discussed as well. Finally, a new method of approaching OCR is introduced, developed, and studied. At the conclusion, the study is summarized, the results are examined, and suggestions are made for continued research. / Department of Computer Science
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Aspects of n-tuple character recognition for a blind reading aidNappey, John Anthony January 1977 (has links)
This thesis reports research conducted into a character recognition system suitable for use in a reading aid for the blind. A brief review of blind reading aids is given, showing the need for a device which is cheap, simple and effective. The structure of a proposed reading aid fulfilling these needs is outlined, with a list of the desired characteristics of each of its subsystems. The remainder of the thesis is concerned with research into just two of these subsystems: the input device and the character recognizer. A detailed review of pattern recognition by the n-tuple method is presented, followed by a description of the experimental techniques used in obtaining real data from a camera system, and in simulating various recognizer structures. The camera system and computer programs developed specifically for the research are described in detail. Several series of experiments are reported, concerned mainly with investigating problems associated directly with the blind reading aid, namely accommodation of multifont printed text and of the tracking errors inherent in data from a hand-held probe. A further series of experiments, aimed at improving the performance of the recognizer within fixed size constraints, i. e., optimisation, has a wider field of application. Finally suggestions are made as to how the recognizer might be implemented in a reading aid, using RAMs, ROMs, or PLAs as the main storage elements.
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Automated license plate recognition a novel approach using spectral analysis and majority vote neural networks /Parthasarathy, Gayathri. January 2006 (has links)
Thesis (M.S.)--University of Nevada, Reno, 2006. / "May, 2006." Includes bibliographical references (leaves 94-99). Online version available on the World Wide Web.
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The application of neural networks to character recognition based on primitive feature detection /Pistacchio, Michael. January 1989 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1989. / "References": leaves 50-51.
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Context sensitive optical character recognition using neural networks and hidden Markov models /Elliott, Steven C. January 1992 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1992. / Typescript. Includes bibliographical references.
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Development of a neural network based software package for the automatic recognition of license plate charactersChen, Songqing. January 1992 (has links)
Thesis (M.S.)--Ohio University, June, 1992. / Title from PDF t.p.
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Advanced correlation-based character recognition applied to the Archimedes Palimpsest /Walvoord, Derek J. January 2008 (has links)
Thesis (Ph.D.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (p. 175-179) and index.
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Constructing a language model based on data mining techniques for a Chinese character recognition system /Chen, Yong, January 2004 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2005.
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The role of the Elementary Perceiver and Memorizer (EPAM) in optical character recognition (OCR)Radvar-Zanganeh, Siasb. January 1994 (has links)
Thesis (M.Comp. Sc.)--Dept. of Computer Science, Concordia University, 1995. / Includes bibliographical references (leaves 119-128) and index. Available also on the Internet.
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