International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Classification of Plants into Families based on Leaf Texture

  • TREY, Zacrada Francoise (Laboratoire de recherche en informatique et telecommunication, INP-HB) ;
  • GOORE, Bi Tra (Laboratoire de recherche en informatique et telecommunication, INP-HB) ;
  • BAGUI, K. Olivier (Laboratoire Instrumentation Image et Spectroscopie, INP-HB) ;
  • TIEBRE, Marie Solange (Laboratoire de Botanique, Universite Felix Houphouet-Boigny)
  • Received : 2021.02.05
  • Published : 2021.02.28
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Abstract

Plants are important for humanity. They intervene in several areas of human life: medicine, nutrition, cosmetics, decoration, etc. The large number of varieties of these plants requires an efficient solution to identify them for proper use. The ease of recognition of these plants undoubtedly depends on the classification of these species into family; however, finding the relevant characteristics to achieve better automatic classification is still a huge challenge for researchers in the field. In this paper, we have developed a new automatic plant classification technique based on artificial neural networks. Our model uses leaf texture characteristics as parameters for plant family identification. The results of our model gave a perfect classification of three plant families of the Ivorian flora, with a determination coefficient (R2) of 0.99; an error rate (RMSE) of 1.348e-14, a sensitivity of 84.85%, a specificity of 100%, a precision of 100% and an accuracy (Accuracy) of 100%. The same technique was applied on Flavia: the international basis of plants and showed a perfect identification regression (R2) of 0.98, an error rate (RMSE) of 1.136e-14, a sensitivity of 84.85%, a specificity of 100%, a precision of 100% and a trueness (Accuracy) of 100%. These results show that our technique is efficient and can guide the botanist to establish a model for many plants to avoid identification problems.

Keywords

References

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