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A New Leaf Venation Detection Technique for Plant Species Classification

  • Hoshang Kolivand
  • Bong Mei Fern
  • Tanzila Saba
  • Mohd Shafry Mohd Rahim
  • Amjad Rehman
Research Article - Computer Engineering and Computer Science
  • 1 Downloads

Abstract

This paper presents a novel approach to classify the leaf shape and to identify plant species using venation detection. The proposed approach consists of five main steps to extract the leaf venation, including canny edge detection, remove leaf boundary, extract curve, and produce hue normalization image and image fusion. Moreover, to localize the edge direction efficiently, the lines that extracted from pre-processing are further divided into smaller segments. Thirty-two leaf images of Malaysian plants are analysed and evaluated with two different datasets, Flavia and Acer. The average accuracy is obtained by 98.6 and 89.83% for Flavia and Acer datasets, respectively. Experimental results show the effectiveness of the proposed approach for shape recognition with high accuracy.

Keywords

Leaf venation Plant species Features extraction Features selection Classification 

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Notes

Acknowledgements

This work is output of the collaboration of Department of Computer Science, Liverpool John Moores University, Liverpool, UK, University Industry Research Laboratory (UIRL), Universiti Teknologi Malaysia UTM, Skudai, Johor, Malaysia, and Machine Learning Research Group [RG-CCIS-2017-06-02] Prince Sultan University Riyadh Saudi Arabia.

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Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceLiverpool John Moores UniversityLiverpoolUK
  2. 2.Department of Computer ScienceUniversiti Tunku Abdul RahmanKajangMalaysia
  3. 3.College of Computer and Information SciencesPrince Sultan UniversityRiyadhSaudi Arabia
  4. 4.Media and Games Innovation Centre of Excellence (MaGIC-X) UTM-IRDA Digital Media Centre, Institute of Human Centred, University Industry Research Laboratory (UIRL)Universiti Teknologi Malaysia (UTM)SkudaiMalaysia
  5. 5.College of Computer and Information SystemsAl Yamamah UniversityRiyadhSaudi Arabia

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