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Document management system using optical character recognition, clustering, watermarking and QR coding algorithms

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Thesis abstract (359.3Kb)
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Date
2021
Author
Censoro, Keith C.
Thesis Adviser
Ojacastro, Rose Leah Joy A.
Defense Panel Chair
Penetrante, Mary O' T.
Defense Panel Member
Quijano, Ma. Christina A.
Balontong, Anrem J.
Cambronero, Pedro Peter Rhys B. Jr.
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Abstract
The Document Management System is a stand-alone desktop application that provides the employees of the Department of Budget and Management Regional Office VI a service that would secure the circulars and memorandum documents. The Document Management System will accept an official document sent by the Central office to be scanned into the system thru a scanning module that will use Optical Character Recognition (OCR). The captured image of the scanned document is converted to text and clustered into supervised keywords to facilitate searching using the Term Frequency-Inverse Document Frequency (TF-IDF) Algorithm. The scanned document will then undergo authentication by imprinting a watermark image and a QR Code using the watermarking algorithm using Text Brush Embedding and a QR Code Model 2 matrix code. The Evolutionary Prototyping model was used throughout the system development process. It has phases where system evaluation is made directly by the evaluators and the system is refined based on feedbacks which fastened the system process.

Employees of the Department of Budget and Management Regional Office VI evaluated the system and based on feedback, the scanned documents that underwent the authentication process was very secured as the watermark and QR code is imprinted on the document accurately.

The features of the system was able to generate a scanned document with watermark and QR Code imprint and was scanned via the verifier that accepted the document as an authenticated and secured copy generated by the system.
Description
Abstract only
URI
https://hdl.handle.net/20.500.12852/1519
Suggested Citation
Censoro, K. C. (2021). Document management system using optical character recognition, clustering, watermarking and QR coding algorithms (Unpublished Master’s thesis). Central Philippine University, Jaro, Iloilo City.
Type
Thesis
Subject(s)
Optical character recognition OCLC - FAST (Faceted Application of Subject Terminology); Document imaging systems OCLC - FAST (Faceted Application of Subject Terminology); Digital watermarking OCLC - FAST (Faceted Application of Subject Terminology); QR codes OCLC - FAST (Faceted Application of Subject Terminology)
Department
School of Graduate Studies
Degree
Master of Science in Computer Science
Shelf Location
GSL Theses 004.72 C332
Physical Description
x, 84 leaves
Collections
  • Master of Science in Computer Science [12]

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