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Generic Object Recognition Using Both Illustration Images and Real-Object Images by CNN

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Advances in Artificial Intelligence and Applied Cognitive Computing

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Abstract

In recent years, the development of robots has been carried out for making human life more convenient and more comfortable along with the development of artificial intelligence. It is necessary for the robot to recognize the surrounding environment. However, in the surrounding environment there are objects other than real objects such as illustrations and paintings. When recognizing an image showing an illustration image with the current object recognition system which learned using real-object images, the recognition rate is very low (about 65%). In this research, we aim to recognize both illustration images and real-object images, and we verified whether the pseudo illustrated image which processed contour processing and the color reduction processing to the real image is effective for the recognition of the illustrated image.

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References

  1. A. Krizhevsky, I. Sutskever, G.E. Hinton, ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems 25 (NIPS 2012), pp. 1097–1105, 2012

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  2. ImageNet: http://www.image-net.org/, 28. December 2016

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  4. https://www.ac-illust.com/?mid=59acd36c5ad15

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Acknowledgments

This work was partially supported by JSPS KAKENHI Grant Number 16 K00311.

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Authors and Affiliations

  1. Department of Intelligent Information Engineering and Science, Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto, Japan

    Hirokazu Watabe & Seiji Tsuchiya

  2. Department of Information Systems, School of Informatics, Daido University, Nagoya, Aichi, Japan

    Misako Imono

Authors
  1. Hirokazu Watabe
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  2. Misako Imono
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  3. Seiji Tsuchiya
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Corresponding author

Correspondence to Misako Imono .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Georgia, Athens, GA, USA

    Hamid R. Arabnia

  2. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada

    Ken Ferens

  3. Business Administration, University of Oviedo, Oviedo, Asturias, Spain

    David de la Fuente

  4. Institute of Informatics Problems, The Russian Academy of Sciences, Moscow, Russia

    Elena B. Kozerenko

  5. Technology and Information systems, Universidad de Castilla La Mancha, Ciudad Real, Ciudad Real, Spain

    José Angel Olivas Varela

  6. Facultad de Informática - CIC PBA, Universidad Nacional de La Plata, La Plata, Argentina

    Fernando G. Tinetti

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Watabe, H., Imono, M., Tsuchiya, S. (2021). Generic Object Recognition Using Both Illustration Images and Real-Object Images by CNN. In: Arabnia, H.R., Ferens, K., de la Fuente, D., Kozerenko, E.B., Olivas Varela, J.A., Tinetti, F.G. (eds) Advances in Artificial Intelligence and Applied Cognitive Computing. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70296-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-70296-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-70295-3

  • Online ISBN: 978-3-030-70296-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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