magistrsko delo
Gregor Jurgec (Author), Iztok Fister (Mentor)

Abstract

V delu predstavljamo postopek stiskanja slik s pomočjo optimizacijskih algoritmov iz dveh različnih družin, tj. evolucijskih algoritmov in algoritmov na osnovi inteligence rojev. V naši raziskavi smo za reševanje zadanega problema uporabili diferencialno evolucijo in optimizacijo s kukavičjim iskanjem. Osnovna algoritma smo izboljšali z adaptacijskimi in hibridizacijskimi metodami. Stiskanje slik smo izvedli s pomočjo množice primitivnih geometrijskih oblik trikotnika. Razvita algoritma smo testirali na realnih primerih stiskanja slik in kakovost rezultatov stiskanja primerjali med seboj.

Keywords

evolucijski algoritmi;inteligenca rojev;diferencialna evolucija;kukavičje iskanje;stiskanje slik;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: G. Jurgec
UDC: 004.421(043.2)
COBISS: 19541526 Link will open in a new window
Views: 1267
Downloads: 153
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Other data

Secondary language: English
Secondary title: IMAGE COMPRESSION WITH NATURE-INSPIRED ALGORITHMS
Secondary abstract: In our thesis we have presented process of image compression using optimization algorithms from two different families, i.e. evolutionary and swarm intelligence based algorithms. In our study, we used differential evolution and cuckoo search for solving our problem. We have improved basic algorithms with self-adaptation and hybridization methods. Compression was performed with a set of primitive geometrical shapes of triangles. Developed algorithms were tested on real cases of image compression and compression quality results were compared with each other.
Secondary keywords: evolutionary algorithms;swarm intelligence;differential evolution;cuckoo search;image compression;
URN: URN:SI:UM:
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages: X, 55 f.
ID: 9134769