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master's thesis
Pasivna detekcija živih lica za sustave prepoznavanja lica
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:010137
Omrčen, Petra
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Omrčen, P. (2023). Pasivna detekcija živih lica za sustave prepoznavanja lica (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:010137

Omrčen, Petra. "Pasivna detekcija živih lica za sustave prepoznavanja lica." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:010137

Omrčen, Petra. "Pasivna detekcija živih lica za sustave prepoznavanja lica." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:010137

Omrčen, P. (2023). 'Pasivna detekcija živih lica za sustave prepoznavanja lica', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 07 February 2025, https://urn.nsk.hr/urn:nbn:hr:168:010137

Omrčen P. Pasivna detekcija živih lica za sustave prepoznavanja lica [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2025 February 07] Available at: https://urn.nsk.hr/urn:nbn:hr:168:010137

P. Omrčen, "Pasivna detekcija živih lica za sustave prepoznavanja lica", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:010137

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Metadata
TitlePasivna detekcija živih lica za sustave prepoznavanja lica
Title (english)Passive Liveness Detection for Face Recognition Systems
AuthorPetra Omrčen
MentorIgor Sunday Pandžić (mentor)
Committee memberIgor Sunday Pandžić (predsjednik povjerenstva)
Committee memberMirko Sužnjević (član povjerenstva)
Committee memberKrešimir Matković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-02-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Sustavi raspoznavanja lica sve se više koriste za identifikaciju i razne kontrole pristupa. Ukoliko se ne koriste dodatne mjere sigurnosti, sustave za raspoznavanje lica bilo bi lako zavarati na način da se ispred kamere postavi slika ili video snimka te osobe. Cilj ovog rada je istraživanje i implementiranje potencijalnih metoda koje rješavaju ovaj problem. Odabrane su tri metode. Dvije se baziraju na analizi boje i teksture slike. Isprobani su različiti prostori boja (RGB, HSV i YCrCB) i deskriptor LBP za izvlačenje korisnih značajki iz slika. Jedna metoda koristi histograme i SVM za klasifikaciju, a druga konvolucijsku neuronsku mrežu koja se ne oslanja samo na ručno izvučene značajke te koristi manje dijelove slike u procesu učenja. Posljednja metoda koristi dubinu slike kako bi odredila radi li se o stvarnoj ili lažnoj slici osobe.
Abstract (english)
Facial recognition systems are increasingly used for identification and various access controls. If additional security measures are not used, it would be easy to fool facial recognition systems by placing a picture or video of that person in front of the camera. The aim of this work is to research and implement potential methods that solve this problem. Three methods were chosen. Two are based on the analysis of the color and texture of the image. Different color spaces (RGB, HSV and YCrCB) and LBP descriptor were used to extract useful features from the image. One method uses histograms and SVM for classification, and the other a convolutional neural network that does not rely only on manually extracted features and uses patches of the image in the learning process. The last method uses the depth of the image to determine whether it is a real or spoof image.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:010137
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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RepositoryFER Repository
Created on2023-07-13 10:25:12

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