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master's thesis
Očitavanje 7-segmentnih identifikacijskih oznaka studenata
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:794956
Zahran, Shadi
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Zahran, S. (2020). Očitavanje 7-segmentnih identifikacijskih oznaka studenata (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:794956

Zahran, Shadi. "Očitavanje 7-segmentnih identifikacijskih oznaka studenata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:794956

Zahran, Shadi. "Očitavanje 7-segmentnih identifikacijskih oznaka studenata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:794956

Zahran, S. (2020). 'Očitavanje 7-segmentnih identifikacijskih oznaka studenata', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:794956

Zahran S. Očitavanje 7-segmentnih identifikacijskih oznaka studenata [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 November 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:794956

S. Zahran, "Očitavanje 7-segmentnih identifikacijskih oznaka studenata", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:794956

Metadata
TitleOčitavanje 7-segmentnih identifikacijskih oznaka studenata
Title (english)Automatic Recognition of 7-Segment Student Identifiers
AuthorShadi Zahran
MentorMarko Čupić (mentor)
Committee memberMarko Čupić (predsjednik povjerenstva)
Committee memberJan Šnajder (član povjerenstva)
Committee memberLeonardo Jelenković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Automatsko očitavanje rukom pisanih brojeva i tekstova na temelju slike je računalno težak problem. Kako bi se u obrazovnim institucijama riješio problem unosa identifikacijskih brojeva, studentima je predočen predložak koji se sastoji od 7-segmentnih znakova kojeg onda oni moraju popuniti sa svojim brojem. U okviru ovog diplomskog rada, istraženi su mogući načini za ostvarivanje jednog sustava za identifikaciju studentskih oznaka sa popunjenih predložaka. U sklopu tog istraživanja, proučene su razne metode segmentacije slike koja je ključni dio obrade slike. Osim toga su proučavane i umjetne neuronske mreže te načini na koji mogu pomoći ovome problemu. Uz segmentaciju slike dobiveni su ulazi za napravljenu neuronsku mrežu koja je onda trenirana te je dobiven model čija je točnost na skupu za testiranje koji sačinjavaju slike od 300 dpi-ja 100%.
Abstract (english)
Automatic handwriting and text recognition are a computationally very difficult problem. Since students in universities have to write their personal identifying numbers during exams or other activities that problem is made simpler by offering them a template consisting of 7-segment characters which they are able to fill in order to form their identifying number, removing the handwriting recognition problem in the process. In this thesis, ways to implement such a system are researched as well as ways to extract data from an image like image segmentation. After performing image segmentation on the filled templates an artificial neural network is developed and trained on the training set. The resulting model is tested on the test set which consisted of 300 dpi images and the model performed exceptionally well with the accuracy of it being at the maximum possible, 100%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:794956
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2023-01-13 10:54:44