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The Importance of Color Spaces for Image Classification Using Artificial Neural Networks: A Review

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12950))

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Abstract

Image classification is one of the most important applications of artificial neural networks in the field of industry and research. In most research work, when implementing ANN-based image classification models, the images used for training and testing are always represented in the RGB color space. But recent articles show that the use of certain color spaces, other than RGB, can lead to better precision in ANN-based image classification models. Thus, in this work, we present an analysis of several relevant research articles about the importance of color spaces for image classification using artificial neural networks. Thus, through the review of these articles, we will evaluate the behavior and efficiency of several ANN architectures, in different image classification contexts, and using images data sets represented in several color spaces. In the end, we not only found that there is a clear influence of the color spaces in the final accuracy of this type of tasks. But, we also found that both the creation of new special ANN architectures, and the creation of new color spaces formed from the combination of others, can lead to an increase in the performance of ANN-based image classification models.

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Authors and Affiliations

  1. Norwegian University of Science and Technology, Gjøvik, Norway

    Ronny Velastegui, Linna Yang & Dong Han

Authors
  1. Ronny Velastegui
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  2. Linna Yang
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  3. Dong Han
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Corresponding author

Correspondence to Ronny Velastegui .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Velastegui, R., Yang, L., Han, D. (2021). The Importance of Color Spaces for Image Classification Using Artificial Neural Networks: A Review. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12950. Springer, Cham. https://doi.org/10.1007/978-3-030-86960-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-86960-1_6

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