A Plant Recognition Approach Using Shape and Color Features in Leaf Images

  • Ali Caglayan
  • Oguzhan Guclu
  • Ahmet Burak Can
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)


Recognizing plants is a vital problem especially for biologists, chemists, and environmentalists. Plant recognition can be performed by human experts manually but it is a time consuming and low-efficiency process. Automation of plant recognition is an important process for the fields working with plants. This paper presents an approach for plant recognition using leaf images. Shape and color features extracted from leaf images are used with k-Nearest Neighbor, Support Vector Machines, Naive Bayes, and Random Forest classification algorithms to recognize plant types. The presented approach is tested on 1897 leaf images and 32 kinds of leaves. The results demonstrated that success rate of plant recognition can be improved up to 96% with Random Forest method when both shape and color features are used.


Leaf recognition shape features color features 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ali Caglayan
    • 1
  • Oguzhan Guclu
    • 1
  • Ahmet Burak Can
    • 1
  1. 1.Department of Computer EngineeringHacettepe UniversityAnkaraTurkey

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