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2020 | OriginalPaper | Chapter

Leaf Recognition Using Prewitt Edge Detection and K-NN Classification

Authors : M. Vilasini, P. Ramamoorthy

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

Publisher: Springer International Publishing

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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.

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Metadata
Title
Leaf Recognition Using Prewitt Edge Detection and K-NN Classification
Authors
M. Vilasini
P. Ramamoorthy
Copyright Year
2020
Publisher
Springer International Publishing
Book
New Trends in Computational Vision and Bio-inspired Computing

Print ISBN: 978-3-030-41861-8

Electronic ISBN: 978-3-030-41862-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-41862-5_155

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