Keywords

IMAGE, RESTORATION, ALIGNMENT, OCR, MULTI-ENGINE, MULTI, ENGINE, MULTIENGINE, OPTICAL, CHARACTER, RECOGNITION, VISUAL, CHARACTER, COMPARISON

Abstract

Previous 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, several aspects to automate and improve the accuracy rate needed further research. This thesis will focus on morphological image preprocessing and morphological text restoration that goes to OCR engines. This method is similar to the one used in restoration partial finger prints. Series of morphological dilating and eroding filters of various mask shapes and sizes were applied to text of different font sizes and types with various noises added. These images were then processed by the OCR engines, and based on these results successful combinations of text, noise, and filters were chosen. The thesis will also deal with the problem of text alignment. Each OCR engine has its own way of dealing with noise and corrupted characters; as a result, the output texts of OCR engines have different lengths and number of words. This in turn, makes it impossible to use spaces a delimiter as a method to separate the words for processing by the voting part of the system. Text aligning determines, using various techniques, what is an extra word, what is supposed to be two or more words instead of one, which words are missing in one document compared to the other, etc. Alignment algorithm is made up of a series of shifts in the two texts to determine which parts are similar and which are not. Since errors made by OCR engines are due to visual misrecognition, in addition to simple character comparison (equal or not), a technique was developed that allows comparison of characters based on how they look.

Notes

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Graduation Date

2006

Semester

Spring

Advisor

Weeks, Arthur

Degree

Master of Science in Electrical Engineering (M.S.E.E.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Degree Program

Electrical Engineering

Format

application/pdf

Identifier

CFE0001060

URL

http://purl.fcla.edu/fcla/etd/CFE0001060

Language

English

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

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