A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network

TL;DR

This paper presents a fast, accurate leaf recognition algorithm using Probabilistic Neural Networks that classifies 32 plant species with over 90% accuracy, employing image processing and principal component analysis.

Contribution

The paper introduces a novel application of PNN with feature extraction and PCA for efficient plant classification.

Findings

Achieved over 90% classification accuracy.

Reduced feature set to 5 principal variables.

Demonstrated fast and easy implementation.

Abstract

In this paper, we employ Probabilistic Neural Network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition algorithm. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.