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Neural Computing and Applications

, Volume 30, Issue 6, pp 1957–1969 | Cite as

Distinguishing paintings from photographs by complexity estimates

  • Adrian Carballal
  • Antonino SantosEmail author
  • Juan Romero
  • Penousal Machado
  • João Correia
  • Luz Castro
Original Article
  • 136 Downloads

Abstract

This study is aimed at exploring the ability of complexity-based metrics to distinguish between paintings and photographs. The proposed features resort to edge detection, compression and entropy estimate methods that are highly correlated with artwork complexity. Artificial neural networks based on these features were trained for this task. The relevance of various combinations of these complexity metrics is also analyzed. The results of the current study indicate that different estimates related to image complexity achieve better results than state-of-the-art feature sets based on color, texture and perceptual edges. The classification success rate achieved is 94.82% on a dataset of 5235 images.

Keywords

Artificial neural networks Complexity estimates Edge detection Feature extraction Image retrieval 

Notes

Acknowledgements

We are very grateful for the reviewers suggestions. This work was supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. GRC2014/049) and the European Fund for Regional Development (FEDER) in the European Union, the Portuguese Foundation for Science and Technology in the scope of project SBIRC (Ref. PTDC/EIA EIA/115667/2009), Xunta de Galicia (Ref. XUGA - PGIDIT - 10TIC105008-PR) and the Spanish Ministry for Science and Technology (Ref. TIN2008-06562/TIN).

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Copyright information

© The Natural Computing Applications Forum 2016

Authors and Affiliations

  • Adrian Carballal
    • 1
  • Antonino Santos
    • 1
    Email author
  • Juan Romero
    • 1
  • Penousal Machado
    • 2
  • João Correia
    • 2
  • Luz Castro
    • 1
  1. 1.Artificial Neural Networks and Adaptive Systems LABUniversity of A CoruñaA CoruñaSpain
  2. 2.CISUC, Department of Informatics EngineeringUniversity of CoimbraCoimbraPortugal

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