Fractal image compression: theory and application
Fractal image compression: theory and application
SBIA '98 Proceedings of the 14th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
The Design of High-Level Features for Photo Quality Assessment
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Photo and Video Quality Evaluation: Focusing on the Subject
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Saliency-enhanced image aesthetics class prediction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Classification of digital photos taken by photographers or home users
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Studying aesthetics in photographic images using a computational approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Inverse mapping with sensitivity analysis for partial selection in interactive evolution
EvoMUSART'13 Proceedings of the Second international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
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One of the problems in evolutionary art is the lack of robust fitness functions. This work explores the use of image compression estimates to predict the aesthetic merit of images. The metrics proposed estimate the complexity of an image by means of JPEG and Fractal compression. The success rate achieved is 72.43% in aesthetic classification tasks of a problem belonging to the state of the art. Finally, the behavior of the system is shown in an image sorting task based on aesthetic criteria.