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master's thesis
Segmentacija rukom pisanih znakova korištenjem klasifikatora
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. urn:nbn:hr:168:642609
Čapalija, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Čapalija, I. (2016). Segmentacija rukom pisanih znakova korištenjem klasifikatora (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:642609

Čapalija, Ivan. "Segmentacija rukom pisanih znakova korištenjem klasifikatora." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:642609

Čapalija, Ivan. "Segmentacija rukom pisanih znakova korištenjem klasifikatora." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:642609

Čapalija, I. (2016). 'Segmentacija rukom pisanih znakova korištenjem klasifikatora', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 02 October 2024, https://urn.nsk.hr/urn:nbn:hr:168:642609

Čapalija I. Segmentacija rukom pisanih znakova korištenjem klasifikatora [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2016 [cited 2024 October 02] Available at: https://urn.nsk.hr/urn:nbn:hr:168:642609

I. Čapalija, "Segmentacija rukom pisanih znakova korištenjem klasifikatora", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:168:642609

Metadata
TitleSegmentacija rukom pisanih znakova korištenjem klasifikatora
Title (english)Handwritten Character Segmentation Using Classifiers
AuthorIvan Čapalija
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberMarko Čupić (član povjerenstva)
Committee memberTomislav Hrkać (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2016-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu su opisana i testirana dva sustava segmentacije rukom pisanih znakova. Prvi sustav se temelji na standardnim metodama računalnog vida kao što su: pomični prozor, predlaganje regija interesa i pretjerana segmentacija. Drugi sustav je baziran na dubokom učenju i gotovo je u cijelosti implementiran standardnim slojevima konvolucijskih neuronskih mreža. Rezultati testiranja oba sustava su prikazani i objašnjeni. Pokazalo se da su lokalizacija i klasifikacija drugog sustava usporedivi s onima iz prvog sustava, ali brzina segmentacije drugog sustava je skoro dva reda veličine veća i to znači da se on može koristiti u stvarnom vremenu. Testiranjem je utvrđeno da oba sustava imaju prostora za poboljšanje, ali veće poboljšanje je moguće ostvariti u drugom pristupu. Izrazito bi teško bilo osposobiti prvi sustav da radi brzo kao drugi.
Abstract (english)
In this thesis, two systems for segmentation of handwritten characters have been elaborated and tested. The first system is based on standard computer vision methods such as: sliding window, region proposal and over-segmentation. The second system is based on deep learning and almost all components of this system are implemented as standard layers used in convolutional neural networks. Testing results of both systems are shown and explained. It is concluded that classification and localization results of both systems are similar, but segmentation process of the second system is almost 100 times faster and that means that the second system can be used in real time. Results of testing showed that both systems can be improved, but bigger improvements can be made on the second system. It would be extremely difficult to improve the speed of the first system to match the speed of the second system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:642609
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 on2018-02-06 08:16:06