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International Conference on Advanced Data Mining and Applications

ADMA 2016: Advanced Data Mining and Applications pp 219–233Cite as

Adopting Hybrid Descriptors to Recognise Leaf Images for Automatic Plant Specie Identification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10086))

Abstract

In recent years, leaf image recognition and classification has become one of the most important subjects in computer vision. Many approaches have been proposed to recognise and classify leaf images relying on features extraction and selection algorithms. In this paper, a concept of distinctive hybrid descriptor is proposed consisting of both global and local features. HSV Colour histogram (HSV-CH) is extracted from leaf images as the global features, whereas Local Binary Pattern after two level wavelet decomposition (WavLBP) is extracted to represent the local characteristics of leaf images. A hybrid method, namely “Hybrid Descriptor” (HD), is then proposed considering both the global and local features. The proposed method has been empirically evaluated using four data sets of leaf images with 256 \(\times \) 256 pixels. Experimental results indicate that the performance of proposed method is promising – the HD outperformed typical leaf image recognising approaches as baseline models in experiments. The presented work makes clear, significant contribution to knowledge advancement in leaf recognition and image classification.

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Author information

Authors and Affiliations

  1. School of Agricultural, Computational and Environmental Sciences, University of Southern Queensland, Toowoomba, Australia

    Ali A. Al-kharaz, Xiaohui Tao, Ji Zhang & Raid Lafta

  2. Department of IT, Technical College of Management, Baghdad Foundation of Technical Education, Baghdad, Iraq

    Ali A. Al-kharaz

Authors
  1. Ali A. Al-kharaz
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  2. Xiaohui Tao
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  3. Ji Zhang
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  4. Raid Lafta
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Corresponding author

Correspondence to Ali A. Al-kharaz .

Editor information

Editors and Affiliations

  1. University of Technology , Sydney, New South Wales, Australia

    Jinyan Li

  2. University of Queensland , Brisbane, Australia

    Xue Li

  3. Beijing Institute of Technology , Beijing, China

    Shuliang Wang

  4. University of Western Australia , Crawley, West Australia, Australia

    Jianxin Li

  5. University of Adelaide , Adelaide, South Australia, Australia

    Quan Z. Sheng

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© 2016 Springer International Publishing AG

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Al-kharaz, A.A., Tao, X., Zhang, J., Lafta, R. (2016). Adopting Hybrid Descriptors to Recognise Leaf Images for Automatic Plant Specie Identification. In: Li, J., Li, X., Wang, S., Li, J., Sheng, Q. (eds) Advanced Data Mining and Applications. ADMA 2016. Lecture Notes in Computer Science(), vol 10086. Springer, Cham. https://doi.org/10.1007/978-3-319-49586-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-49586-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49585-9

  • Online ISBN: 978-3-319-49586-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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