Learning and perceiving colors haptically
Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility
Supervised Image Classification by SOM Activity Map Comparison
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Informational Aesthetics Measures
IEEE Computer Graphics and Applications
Expectation-Maximization x Self-Organizing Maps for Image Classification
SITIS '08 Proceedings of the 2008 IEEE International Conference on Signal Image Technology and Internet Based Systems
IEEE Transactions on Information Theory
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Paintings have some sensibility information to human hearts. It is expected in paintings to process such sensibility information by computers effectively. For appreciation of paintings, grouping of paintings with similar sensitivity will be helpful to visitors as in painting gallery. In this paper, we developed a distance measure to group and classify similar paintings. Further, we applied the self organizing method (SOM) by two layered neural network to classify paintings. Then, the attributes of the sensibility of paintings are checked first. Next, color attributes of paintings are also checked. Paintings data with these attributes were computed by applying these techniques. Relatively well grouped results for the classification of paintings were obtained by the proposed method.