diplomsko delo
Žiga Rot (Author), Vitomir Štruc (Mentor)

Abstract

V tem delu predstavimo izvedbo mehanizma, ki iz slik očesa izloča ožilje beločnice – biometrično karakteristiko, ki se lahko uporabi v sistemih za razpoznavanje šarenice za izboljšanje zanesljivosti in natančnosti razpoznavanja. Model sestavljata dve stopnji. Prva skrbi za izločanje območja zanimanja – beločnice, iz katere nato druga stopnja segmentira ožilje. Našo izvedbo utemeljimo z dvema eksperimentoma. V prvem pokažemo vpliv izločanja območja zanimanja na končni izhod. V drugem prikažemo razliko v uspešnosti segmentacije med enorazredno in večrazredno segmentacijo beločnice.

Keywords

segmentacija slik;ožilje beločnice;globoke konvolucijske nevronske mreže;U-net;univerzitetni študij;Elektrotehnika;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FE - Faculty of Electrical Engineering
Publisher: [Ž. Rot]
UDC: 004.932.72:611.841(043.2)
COBISS: 120224771 Link will open in a new window
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Downloads: 11
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Other data

Secondary language: English
Secondary title: Segmentation of ocular vasculature from visual data with a deep convolutional network
Secondary abstract: This thesis presents the implementation of a model that can extract scleral vasculature from image data – a biometric feature which can be used in iris-based biometric recognition systems to enhance robustness and accuracy. The model consists of two stages. The first stage is used for extraction of the region of interest – the sclera, from which then the next stage segments the vascular structure. We justify our design with two experiments. In the first one, we show the impact of prior extraction of the region of interest on the final output. In the second one, we present the difference in segmentation quality between binary and multi-class versions of sclera segmentation.
Secondary keywords: image segmentation;sclera vascularity;deep convolutional neural networks;U-net;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000313
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za elektrotehniko
Pages: XVI, 35 str.
ID: 16372639