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Title:Aplikacija za pregledovanje in podpisovanje slikovnih dokumentov PDF s pomočjo optičnega prepoznavanja besedila : diplomsko delo
Authors:ID Kepe, Igor (Author)
ID Brest, Janez (Mentor) More about this mentor... New window
ID Bošković, Borko (Comentor)
Files:.pdf UN_Kepe_Igor_2022.pdf (2,57 MB)
MD5: A1D771BF2662F71A2F18510C2005E08E
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu smo razvili aplikacijo, ki bo pohitrila in olajšala podpisovanje dokumentov PDF. Implementirana je v programskem jeziku Python, optično prepoznavanje besedila pa je izvedeno z uporabo odprtokodne knjižnice Tesseract. Aplikacija je namenjena podpisovanju dokumentov PDF s slikovnimi in certificiranimi digitalnimi podpisi ter prepoznavanju besedila iz slik in slikovnih dokumentov PDF. Poleg tega nam lahko služi tudi kot enostavni urejevalnik besedila. V veliko pomoč je aplikacija lahko študentom ter vsem, ki se pri delu srečujejo z digitalizacijo ali arhiviranjem dokumentov. Prav tako vsem tistim, ki potrebujejo prepoznavo besedila natisnjenih ali skeniranih dokumentov.
Keywords:Optično prepoznavanje znakov, Tesseract OCR, digitalni podpis, Python, dokument PDF
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[I. Kepe]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (XI, 49 f.))
PID:20.500.12556/DKUM-82193 New window
UDC:004.93(043.2)
COBISS.SI-ID:128934403 New window
Publication date in DKUM:17.10.2022
Views:654
Downloads:62
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:28.07.2022

Secondary language

Language:English
Title:Application for viewing and signing image-only PDF documents using optical character recognition
Abstract:In this thesis, we developed an application that will speed up and facilitate the process of signing PDF documents. It is implemented in the Python programming language where optical character recognition is performed through the use of open source Tesseract library. The application is used for signing PDF documents with electronic and certified digital signatures as well as for recognizing text within images and image-only PDF documents. In addition, it can also serve as a simple text editor. The application can be of a great help to students and anyone who encounters digitization or archiving of documents at work. Furthermore, it facilitates individuals who need text recognition of printed or scanned documents.
Keywords:Optical character recognition, Tesseract OCR, digital signature, Python, PDF document


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