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Review on Techniques for Plant Leaf Classification and Recognition

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Department of Bioprocess and Polymer Engineering, School of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, UTM Skudai, Johor Bahru 81310, Johor, Malaysia
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Metabolites Profiling Laboratory, Institute of Bioproduct Development, Universiti Teknologi Malaysia, UTM Skudai, Johor Bahru 81310, Johor, Malaysia
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Robotic and Computer Aided Detection Laboratory, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn, Parit Raja, Batu Pahat 86400, Johor, Malaysia
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Department of Chemical Engineering, School of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, UTM Skudai, Johor Bahru 81310, Johor, Malaysia
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Author to whom correspondence should be addressed.
Computers 2019, 8(4), 77; https://doi.org/10.3390/computers8040077
Received: 2 September 2019 / Revised: 3 October 2019 / Accepted: 16 October 2019 / Published: 21 October 2019
Plant systematics can be classified and recognized based on their reproductive system (flowers) and leaf morphology. Neural networks is one of the most popular machine learning algorithms for plant leaf classification. The commonly used neutral networks are artificial neural network (ANN), probabilistic neural network (PNN), convolutional neural network (CNN), k-nearest neighbor (KNN) and support vector machine (SVM), even some studies used combined techniques for accuracy improvement. The utilization of several varying preprocessing techniques, and characteristic parameters in feature extraction appeared to improve the performance of plant leaf classification. The findings of previous studies are critically compared in terms of their accuracy based on the applied neural network techniques. This paper aims to review and analyze the implementation and performance of various methodologies on plant classification. Each technique has its advantages and limitations in leaf pattern recognition. The quality of leaf images plays an important role, and therefore, a reliable source of leaf database must be used to establish the machine learning algorithm prior to leaf recognition and validation. View Full-Text
Keywords: leaf; pattern recognition; artificial neural network; probabilistic neural network; convolutional neural network; k-nearest neighbor; support vector machine leaf; pattern recognition; artificial neural network; probabilistic neural network; convolutional neural network; k-nearest neighbor; support vector machine
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Azlah, M.A.F.; Chua, L.S.; Rahmad, F.R.; Abdullah, F.I.; Wan Alwi, S.R. Review on Techniques for Plant Leaf Classification and Recognition. Computers 2019, 8, 77.

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