diplomsko delo
Dario Šnajder (Author), Milan Zorman (Mentor)

Abstract

V diplomskem delu smo podrobno raziskali algoritem k-means, ki v kontekstu strojnega učenja spada v skupino algoritmov nenadzorovanega učenja. Proučili smo probleme in možnost iskanja dominantnih barv na digitalni fotografiji z uporabo omenjenega algoritma. Raziskali smo različne barvne modele in iskanje barvnih harmonij. Izdelali smo aplikacijo, ki omogoča fotografiranje (npr. oblačil), iskanje dominantnih barv in določanje različnih barvnih harmonij.

Keywords

strojno učenje;k-means;barvni modeli;dominantne barve;barvne harmonije;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: D. Šnajder
UDC: 004.85.021(043.2)
COBISS: 19844374 Link will open in a new window
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Downloads: 74
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Other data

Secondary language: English
Secondary title: USING MACHINE LEARNING METHODS FOR DETERMINING DOMINANT COLOR ON DIGITAL PHOTOGRAPHY
Secondary abstract: In this thesis we carried out a detailed research of k-means algorithm, which in the context of machine learning is classified into the group of unsupervised learning algorithms. We examined the possibilities for determining dominant color in the digital photography using the k-means algorithm. We also researched various color models and how to find color harmonies. In the end, an application was implemented with which the user can take a picture (e.g. of clothing), find dominant colors and determine the color harmonies.
Secondary keywords: machine learning;ak-means;color models;dominant colors;harmonies;
URN: URN:SI:UM:
Type (COBISS): Undergraduate thesis
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informatika
Pages: X, 63 f.
ID: 9161405