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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 56 for “"optical character recognition"”.
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A CARTOGRAPHIC OPTICAL CHARACTER RECOGNITION SYSTEM
This thesis describes an Optical Character Recognition system for use in a cartographic application. The system is primarily intended to recog-nize and digitize both machine printed navigational chart sounding values and hand-printed field sheet sounding values. The system consists of a precision …
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Optical character recognition for reading machine applications.
Massachusetts Institute of Technology. Dept. of Electrical Engineering. Thesis. 1965. Ph.D.
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Assist channel coding for improving optical character recognition
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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System design - optical character recognition with weighted area masks.
Thesis: M.S., Massachusetts Institute of Technology, Department of Mechanical Engineering, 1965
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The untrusted computer problem and camera based authentication using optical character recognition
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
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Text-image Restoration And Text Alignment For Multi-engine Optical Character Recognition Systems
… research showed that combining three different optical character recognition (OCR) engines (ExperVision® OCR, Scansoft OCR, and Abbyy® OCR) results using voting algorithms will get higher accuracy rate than each of the engines individually. While a voting algorithm has been realized, …
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The influence of optical character recognition quality on the robustness of semantic encoding
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms
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The role of the Elementary Perceiver and Memorizer (EPAM) in optical character recognition (OCR)
… objects of the EPAM model are defined as characters, and words of the English language are defined as the upper bound on the complexity of the objects. In this way the model is tested under: (1) One level of object complexity. (2) A large base of objects with a variable length feature set. …
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Data Capture Automation in the South African Deeds Registry using Optical Character Recognition (OCR)
… 98.3% for the fields extracted from typed text characters. This is within the accuracy range of manual data capture. A secondary quality check, which is currently done on manual data capture, would still be necessary to ensure accuracy of inputs. Overall it appears that this application would be …
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Autonomous Repair Of Optical Character Recognition Data Through Simple Voting And Multi-dimensional Indexing Techniques
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 …
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Image recognition using the Eigenpicture Technique (with specific applications in face recognition and optical character recognition)
In the first part of this dissertation, we present a detailed description of the eigenface technique first proposed by Sirovich and Kirby and subsequently developed by several groups, most notably the Media Lab at MIT. Other significant contributions have been made by Rockefeller University, whose …
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A comparative study of neural network algorithms.
… Neural network models are investigated for Optical Character Recognition application and a Multi-layer Feed forward neural network is trained using a Fast training algorithm. Then the fast training algorithm is compared with the delta rule training algorithm. The various neural network …
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A relational post-processing approach for forms recognition
Optical Character Recognition (OCR) is used to convert paper documents into electronic form. Unfortunately the technology is not perfect and the output can be erroneous. Conversion then is generally augmented by manual error detection and correction procedures which can be very costly; One approach …
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Autotag: A tool for creating structured document collections from printed materials
Today's optical character recognition (OCR) devices ordinarily are not capable of delimiting or "marking up" specific structural information about the document such as the title, its authors, and titles of sections. Such information appears in the OCR device output, but would require a human to go …
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Predictor of OCR accuracy using statistical techniques
Systems that predict optical character recognition (OCR) accuracy of an input image by a given OCR system were developed. Seven features associated with image defects were identified and utilized. Two kinds of nonparametric classification engines, the nearest neighbor rule-based and neural …
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The use of synthesized images to evaluate the performance of Ocr devices and algorithms
… images can be used to predict the performance of Optical Character Recognition (OCR) algorithms and devices. The value of this research lies in reducing the considerable costs associated with preparing test images for OCR research. The paper reports on a series of experiments in which synthesized …
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Adaptive restoration of text images containing touching and broken characters
… automated data entry is generally performed by optical character recognition (OCR) systems. To make these systems practical, reliable OCR systems are essential. However, distortions in document images cause character recognition errors, thereby, reducing the accuracy of OCR systems. In document …
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An Artificial Intelligence Based Approach to Automate Document Processing in Business Area
… to improve operational efficiency. With Optical Character Recognition (OCR) and machine learning techniques, businesses are able to apply Artificial Intelligence (AI) to automate the process. However, introducing an AI application to business is challenging; it is easy to fail because of …
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Mathematical Expression Detection and Segmentation in Document Images
… are employed in order to enhance the accuracy of optical character recognition (OCR) in document images. Type-specific document layout analysis involves localizing and segmenting specific zones in an image so that they may be recognized by specialized OCR modules. Zones of interest include titles, …
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Evaluation of page quality using simple features
A classifier to determine page quality from an Optical Character Recognition (OCR) perspective is developed. It classifies a given page image as either "good" (i.e. high OCR accuracy is expected) or "bad" (i.e., low OCR accuracy expected). The classifier is based upon measuring the amount of white …
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