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master's thesis
Usporedba aplikacija za optičko prepoznavanje znakova
2021. urn:nbn:hr:162:964713
Jelovčić, Sunčana
University of Zadar
Department of Information Sciences

Cite this document

Jelovčić, S. (2021). Usporedba aplikacija za optičko prepoznavanje znakova (Master's thesis). Zadar: University of Zadar. Retrieved from https://urn.nsk.hr/urn:nbn:hr:162:964713

Jelovčić, Sunčana. "Usporedba aplikacija za optičko prepoznavanje znakova." Master's thesis, University of Zadar, 2021. https://urn.nsk.hr/urn:nbn:hr:162:964713

Jelovčić, Sunčana. "Usporedba aplikacija za optičko prepoznavanje znakova." Master's thesis, University of Zadar, 2021. https://urn.nsk.hr/urn:nbn:hr:162:964713

Jelovčić, S. (2021). 'Usporedba aplikacija za optičko prepoznavanje znakova', Master's thesis, University of Zadar, accessed 02 April 2025, https://urn.nsk.hr/urn:nbn:hr:162:964713

Jelovčić S. Usporedba aplikacija za optičko prepoznavanje znakova [Master's thesis]. Zadar: University of Zadar; 2021 [cited 2025 April 02] Available at: https://urn.nsk.hr/urn:nbn:hr:162:964713

S. Jelovčić, "Usporedba aplikacija za optičko prepoznavanje znakova", Master's thesis, University of Zadar, Zadar, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:162:964713

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Metadata
TitleUsporedba aplikacija za optičko prepoznavanje znakova
Title (english)Comparison of optical character recognition applications
AuthorSunčana Jelovčić
MentorMirko Duić (mentor)
Committee memberKrešimir Zauder (predsjednik povjerenstva)
Committee memberAnte Panjkota (član povjerenstva)
Committee memberMirko Duić (član povjerenstva)
GranterUniversity of Zadar
(Department of Information Sciences)
Zadar
Defense date and country2021-02-25, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract
Cilj ovog rada je predstavljanje procesa optičkog prepoznavanja znakova i njegove primjene u praksi. Kako je optičko prepoznavanje znakova pretvaranje analognog dokumenta u pretraživu digitalnu inačicu, u prvom teoretskom dijelu rada objašnjen je pojam digitalizacije te su predstavljeni pojedini projekti i inicijative digitalizacije. Proces optičkog prepoznavanja znakova isprepliće se sa nekoliko srodnih disciplina od kojih su u radu ukratko objašnjene sljedeće: prepoznavanje uzoraka, računalni... More vid te strojno učenje. Teoretski dio rada također opisuje osam glavnih komponenti procesa optičkog prepoznavanja znakova: optičko skeniranje, segmentiranje regija slike, pretprocesiranje, normalizacija, segmentacija, reprezentacija, ekstrahiranje značajki te poučavanje i prepoznavanje. Potom su predstavljene aplikacije za optičko prepoznavanje znakova te je napravljeno istraživanje usporedbe rada u aplikacijama ABBYY FineReader 15, Free OCR-u, Google Drive OCR, I2OCR-u i Convertio. U istraživanju je napravljena usporedba osobina i uspješnosti pet različitih aplikacija za optičko prepoznavanje znakova. Provedena je rasprava o dobivenim rezultatima te su na temelju uvida iz istraživanja i analizirane teorije predstavljena zaključna razmatranja. Less
Abstract (english)
The aim of this paper is to resolve what exactly lies behind the optical character recognition process, what its components are, and how it looks in practice. An optical character recognition, in simple words is translating an analog document into a searchable digital version and the concept of digitization is explained as the root part of the theoretical part of the paper, and what are the projects and initiatives of digitization that would not exist without optical character recognition.... More This process is interwoven with several related disciplines, of which the pattern recognition, computer vision, and machine learning are briefly explained in the paper. The theoretical part of the paper is formulated around a description of eight major components of the optical character recognition process: optical scanning, segmentation of image regions, preprocessing, normalization, segmentation, representation, feature extraction, and teaching and recognition. Although most of the literature is mathematically based, the components of optical character recognition are mathematically illustrated to the limit understandable to all. Optical Character Recognition applications were then introduced and a comparison study was performed on ABBYY FineReader 15, Free OCR, Google Drive OCR, I2OCR and Convertio applications. The methodology used in the research is a qualitative comparison of five different optical character recognition applications and a quantitative comparison of how many errors were made and how many languages were included in the architecture of each application. After the research, a discussion of the results was conducted and conclusions were drawn based on the research and the theory analyzed. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:162:964713
Study programmeTitle: Library and Information Science
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra informacijskih znanosti (magistar/magistra informacijskih znanosti)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-04-21 10:14:38
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