Award Date

1-1-2003

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Committee Member

Kazem Tagva

Number of Pages

36

Abstract

Optical Recognition Technology is typically used to convert hard copy printed material into its electronic form. Many presentational artifacts such as end-of-line hyphenations, running headers and footers are literally converted. These artifacts can possibly hinder proximity and exact match searching; This thesis develops an algorithm to extract running headers and footers from electronic documents generated by OCR. This method associates each page of the document with its neighboring pages and detects the headers and footers by comparing the page with its neighboring pages. Experiments are also taken to test the effectiveness of these algorithms.

Keywords

Documents; Footers; Headers; Identification; Noisy

Controlled Subject

Computer science

File Format

pdf

File Size

1075.2 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

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Rights

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