Abstract
Automatically quantifying the aesthetic appeal of images is an interesting problem in computer science and image processing. In this paper, we incorporate aesthetic properties and convert them into computable image features for classifying photographs taken by amateur and professional photographers. In particular, color histograms, spatial edge distribution, and repetition identification are used as features. Results of experiments on professional and amateur photograph data sets confirm the discriminative power of these features.
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