International Conference on Computer Analysis of Images and Patterns

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

Leaf-Based Plant Identification Through Morphological Characterization in Digital Images

  • Arturo Oncevay-Marcos
  • Ronald Juarez-Chambi
  • Sofía Khlebnikov-Núñez
  • César Beltrán-Castañón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9257)


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.


Leaf-based plant identification Complex networks Multi-scale fractal dimension Haralick’s descriptors Color moments 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Arturo Oncevay-Marcos
    • 1
  • Ronald Juarez-Chambi
    • 1
  • Sofía Khlebnikov-Núñez
    • 1
  • César Beltrán-Castañón
    • 1
  1. 1.Department of Engineering, Research Group on Pattern Recognition and Applied Artificial IntelligencePontificia Universidad Católica Del PerúLimaPerú

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