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Leaf Recognition Using Prewitt Edge Detection and K-NN Classification

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • M. Vilasini

    (KPR Institute of Engineering and Technology)

  • P. Ramamoorthy

    (KPR Institute of Engineering and Technology)

Abstract

Leaf species identification leads to multitude of societal applications. There is enormous research in the lines of plant identification using pattern recognition. With the help of robust algorithms for leaf identification, rural medicine has the potential to reappear as like the previous decades. This paper discusses Prewitt k-NN for leaf species identification from white background. Variations of the model over the features like traditional shape, texture, color and venation apart from the other miniature features of uniformity of edge patterns, leaf tip, margin and other statistical features are explored for efficient leaf classification.

Suggested Citation

  • M. Vilasini & P. Ramamoorthy, 2020. "Leaf Recognition Using Prewitt Edge Detection and K-NN Classification," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1507-1515, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_155
    DOI: 10.1007/978-3-030-41862-5_155
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