Language: | Slovenian |
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Year of publishing: | 2016 |
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 |
Views: | 1267 |
Downloads: | 153 |
Average score: | 0 (0 votes) |
Metadata: |
Secondary language: | English |
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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 |