Thesis Details

Analýza konvolučních neuronových sítí pro detekci a klasifikaci poškození otisku prstu

Master's Thesis Student: Fořtová Kateřina Academic Year: 2021/2022 Supervisor: Kanich Ondřej, Ing., Ph.D.
English title
Analysis of Convolutional Neural Networks for Detection and Classification of Damages in Fingerprint Images
Language
Czech
Abstract

The aim of this Master's thesis is to analyze detection and classification approaches using convolutional neural networks on the problem of fingerprint damage. The first part of the thesis deals with the study of literature related to biometrics and fingerprint processing with emphasis on possible diseases that may affect the fingertip area. Subsequently, the thesis focuses on neural network-based recognition. The thesis describes the architectures of convolutional neural networks and object detection approaches up to the latest research. Several detection methods for detection and classification of skin diseases affecting fingertip are proposed using modern architectures, different types of backbone networks and detection methods. Eight models based on four different detection and classification approaches are chosen for the experiments. Subsequently, each model is trained several times using configuration parameter adjustments. The models are assessed on the basis of various metrics and compared in terms of the use of the backbone network and the chosen method for detection. The best result of 76.875 % was achieved in the test of correctly detected and classified area on real fingerprint images. The most problematic disease for detection and classification was atopic eczema, whose symptoms can manifest in many ways.

Keywords

skin diseases, fingerprints, convolutional neural networks, detection, classification

Department
Degree Programme
Files
Status
defended, grade B
Date
21 June 2022
Reviewer
Committee
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY FIT BUT), předseda
Bidlo Michal, Ing., Ph.D. (DCSY FIT BUT), člen
Burgetová Ivana, Ing., Ph.D. (DIFS FIT BUT), člen
Lengál Ondřej, Ing., Ph.D. (DITS FIT BUT), člen
Matoušek Radomil, doc. Ing., Ph.D. (IACS FME BUT), člen
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Citation
FOŘTOVÁ, Kateřina. Analýza konvolučních neuronových sítí pro detekci a klasifikaci poškození otisku prstu. Brno, 2022. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2022-06-21. Supervised by Kanich Ondřej. Available from: https://www.fit.vut.cz/study/thesis/25006/
BibTeX
@mastersthesis{FITMT25006,
    author = "Kate\v{r}ina Fo\v{r}tov\'{a}",
    type = "Master's thesis",
    title = "Anal\'{y}za konvolu\v{c}n\'{i}ch neuronov\'{y}ch s\'{i}t\'{i} pro detekci a klasifikaci po\v{s}kozen\'{i} otisku prstu",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2022,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/25006/"
}
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