diplomska naloga
Simon Kegljevič (Author), Andrej Dobrovoljc (Mentor)

Abstract

Analiza in primerjava obstoječih OCR razvojnih programskih paketov

Keywords

optična prepoznava znakov;digitalizacija;OCR;OCR SDK rešitve;ABBYY;Tesseract;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: FIŠ - Faculty of Information Studies
Publisher: [S. Kegljevič]
UDC: 004.352.242:004.42(043.2)
COBISS: 2048221971 Link will open in a new window
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Downloads: 0
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Other data

Secondary language: English
Secondary abstract: At the moment, optical character recognition technology is quite well established and useful in some fields of work. Nonetheless we can try and find new ways of successful implementation on new areas, where OCR is not yet present. Use of this technology on new areas will also mean a new market opportunity for a company, which specializes in digitalization and enterprise content management. Based on needs of one such company, we analyzed multiple solutions, which can be used to implement OCR technology in our own programs. Our client wants to implement OCR technology for use in small or medium sized companies on Slovenian market. Thesis is split in two parts. Theoretical part includes wide review of OCR technology along with its supporting processes. Practical part involves analysis of twelve OCR solutions with two open source solutions included. Solutions are rated based on sixteen criteria. Criteria are set according to our clients input, other important functionalities and supporting processes of OCR technology. Out of twelve solutions, eight of them met the requirements of our client and three of the most optimal solutions are picked for advanced testing.
Secondary keywords: Optical character recognition;digitalization;OCR SDK solutions;ABBYY;Tesseract;
Type (COBISS): Bachelor thesis/paper
Thesis comment: Fakulteta za informacijske študije v Novem mestu
Source comment: Na ov.: Diplomska naloga : visokošolskega strokovnega študijskega programa prve stopnje;
Pages: 65 str.
ID: 10950626
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