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International Conference on Computer Analysis of Images and Patterns

CAIP 2015: Computer Analysis of Images and Patterns pp 326–335Cite as

Leaf-Based Plant Identification Through Morphological Characterization in Digital Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9257))

Abstract

The plant species identification is a manual process performed mainly by botanical scientists based on their experience. In order to improve this task, several plant classification processes has been proposed applying pattern recognition. In this work, we propose a method combining three visual attributes of leaves: boundary shape, texture and color. Complex networks and multi-scale fractal dimension techniques were used to characterize the leaf boundary shape, the Haralick’s descriptors for texture were extracted, and color moments were calculated. Experiments were performed on the ImageCLEF 2012 train dataset, scan pictures only. We reached up to 90.41% of accuracy regarding the leaf-based plant identification problem for 115 species.

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Author information

Authors and Affiliations

  1. Department of Engineering, Research Group on Pattern Recognition and Applied Artificial Intelligence, Pontificia Universidad Católica Del Perú, Lima, Perú

    Arturo Oncevay-Marcos, Ronald Juarez-Chambi, Sofía Khlebnikov-Núñez & César Beltrán-Castañón

Authors
  1. Arturo Oncevay-Marcos
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  2. Ronald Juarez-Chambi
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  3. Sofía Khlebnikov-Núñez
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  4. César Beltrán-Castañón
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Corresponding author

Correspondence to Arturo Oncevay-Marcos .

Editor information

Editors and Affiliations

  1. University of Malta, Msida, Malta

    George Azzopardi

  2. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

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Oncevay-Marcos, A., Juarez-Chambi, R., Khlebnikov-Núñez, S., Beltrán-Castañón, C. (2015). Leaf-Based Plant Identification Through Morphological Characterization in Digital Images. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9257. Springer, Cham. https://doi.org/10.1007/978-3-319-23117-4_28

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  • DOI: https://doi.org/10.1007/978-3-319-23117-4_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23116-7

  • Online ISBN: 978-3-319-23117-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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