An Implementation of Leaf Recognition System Based on Leaf Contour and Centroid for Plant Classification

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 214)

Abstract

In this paper, we propose a leaf recognition system based on the leaf contour and centroid that can be used for plant classification. The proposed approach uses frequency domain data by performing a Fast Fourier transform (FFT) for the leaf recognition system. Twenty leaf features were extracted for leaf recognition. First, the distance between the centroid and all points on the leaf contours were calculated. Second, an FFT was performed using the calculated distances. Ten features were extracted using the calculated distances, FFT magnitude, and its phase. Ten features were also extracted based on the digital morphological features using four basic geometric features and five vein features. To verify the validity of the approach, images of 1907 leaves were used to classify 32 kinds of plants. In the experimental results, the proposed leaf recognition system showed an average recognition rate of 95.44 %, and we can confirm that the recognition rate of the proposed advanced leaf recognition method was better than that of the existed leaf recognition method.

Keywords

Leaf recognition Plant classification Leaf feature extraction Fast fourier transform (FFT) 

Notes

Acknowledgments

This research was supported by MKE, Korea under ITRC NIPA-2012-(H0301-12-3001) and PRCP through NRF of Korea, funded by MEST (2012-0005861).

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwonSouth Korea
  2. 2.Department of Railway Operation System EngineeringKorea National University of TransportationUiwang-siSouth Korea

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