Pregled bibliografske jedinice broj: 1264554
Frequency and Texture Features for Iris Recognition
Frequency and Texture Features for Iris Recognition // 30th Telecommunications Forum, TELFOR 2022 - Proceedings, 2022
Beograd: Institute of Electrical and Electronics Engineers (IEEE), 2022. str. 23-31 doi:10.1109/TELFOR56187.2022.9983787 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1264554 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Frequency and Texture Features for Iris Recognition
Autori
Tuba, Una ; Tuba, Eva ; Capor Hrošik, Romana ; Tuba, Milan ; Veinović, Mladen
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
30th Telecommunications Forum, TELFOR 2022 - Proceedings, 2022
/ - Beograd : Institute of Electrical and Electronics Engineers (IEEE), 2022, 23-31
ISBN
9781665472722
Skup
30th Telecommunications Forum, TELFOR 2022 - Proceedings
Mjesto i datum
Beograd, Srbija, 15.11.2022. - 16.11.2022
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
iris recognition ; support vector machine ; local binary pattern ; discrete cosine transformation ; frequency domain ; digital image processing
Sažetak
Digital images and digital image processing have become a vital part of numerous applications, in every day life, science, security, health, etc. The iris of the human eye is a great biometric parameter that can be used for a person’s identification due to its richness and uniqueness in texture and other features. In this paper, a simple method based on the local binary pattern as a texture descriptor and frequency coefficients is proposed. After extracting the eye region, the iris region is found and features are calculated for that region of interest. A support vector machine is used for classification. The proposed method is tested on a well-known CASIA Interval-v4 dataset and the results are improved compared to methods that only use one of these features or a different set of features.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
