Statistical Image Analysis for Image Evolution

This thesis is focused on using genetic programming to evolve images based on lightweight features extracted from a given target image. The main motivation of this thesis is research by Lombardi et al. in which an image retrieval system is developed based on lightweight statistical features of images for comparing and classifying them in painting style categories; primarily based on color matching. In this thesis, automatic fitness scoring of variations of up to 17 lightweight image features using many-objective fitness evaluation was used to evolve textures. Evolved results were shown to have similar color characteristics to target images. Although a human survey was conducted to confirm those results, it was inconclusive.

Name thesis:degree_name

M.Sc. Computer Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Faculty of Mathematics and Science

Department dc:contributor.department

Department of Computer Science

Grantor

Brock University

Year dc:date.issued

2016

Author dc:creator

• Salimi, Elham

• Image analysis, Image evolution, Evolutionary arts, Statistical analysis, Lightweight image retrieval

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/10464/10707

OAI identifier oai:identifier

oai:brocku.scholaris.ca:10464/10707