Gručenje umetniških slik na podlagi njihovih značilnic : diplomsko delo

Vesel, Nejc (author), Šajn, Luka (mentor), Solina, Franc (comentor)

V tej diplomski nalogi želimo preizkusiti metodo, ki nam omogoči, da s pomočjo računalniške analize sliko pripišemo določenemu slikarju. Testiramo dva načina. Pri prvem pristopu želimo identificirati slikarja glede na način, s katerim preslika človeške obrazne poteze iz fotografije na naslikan portret. Zanima nas, ali so razlike v obraznih razmerjih na fotografiji in sliki statistično pomembne. Pri drugi metodi vsako sliko opišemo z vektorjem značilnic. Značilnice obsegajo barvo, teksturo in dimenzije slike, katerih kombinacija tvori vektor značilnic. Princip testiramo na 3 slikarjih z različnimi stili. Za vsakega od njih imamo množico desetih testnih slik. Zanima nas, ali lahko z gručenjem sliko pravilno pripišemo slikarju samo na podlagi teh vektorjev značilnic.

• Language: Slovenian
• Keywords: računalniški vid, umetnost, detekcija obraza, primerjava umetniških slik, klasifikacija, klasifikacija umetnikov
• Work type: Bachelor thesis/paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FRI - Faculty of Computer and Information Science
• Publisher: [N. Vesel]
• Year: 2015
• Number of pages: 52 str.
• PID: 20.500.12556/RUL-72136
• COBISS.SI-ID: 1536458179
• Publication date in RUL: 04.09.2015

VESEL, Nejc, 2015, Gručenje umetniških slik na podlagi njihovih značilnic : diplomsko delo [online]. Bachelor’s thesis. N. Vesel. [Accessed 24 March 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=72136

Secondary language

• Language: English
• Title: Artwork classification based on image features

Abstract

In this thesis we are trying to discover a method that allows us to attribute a painting to a particular artist with the help of image analysis. We are testing two methods. In the first one, we are trying to identify the style of a painter by analysing the way in which he translates a human face from a photograph into a painting. We are testing whether the differences on facial proportions in photographs and paintings are statistically significant. With the other method, we describe every painting with a set of features. The features look at the image color, texture and dimensions to form a feature vector. We test this on 10 pictures for each of the 3 painters with different styles. We are trying to test, whether we can correctly attribute these paintings to a painter just with these feature vectors.

• Keywords: computer vision, art, face detection, artwork comparison, classification, artist classification