Thursday 28th of March 2024
 

Plant Leaves Recognition and Classification Model Based on Image Features and Neural Network


Hong Fang and Huijie Li

In this paper, on the basis of image processing, plant leaves are respectively extracted 7 HU invariant moment eigenvalues, three shape eigenvalues and eight texture eigenvalues based on gray level co-occurrence matrix. Then the paper adopts BP network, which has been optimized by L-M algorithm to identify the classes of the plant leaves based on 7, 10 and 18 eigenvalues. The experimental results show that the classification effect of 18 eigenvalues is the best, the average recognition rate of which is 100%, providing a fast and effective method for the identification of plant species.

Keywords: Image processing, Feature extraction, L-M algorithm, BP neural network, Classification

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ABOUT THE AUTHORS

Hong Fang
Associate Professor of Tianjin Agricultural University in the Mathematics Department, the Director of Tianjin Industrial and Applied Mathematics Association, mainly engaged in the teaching of mathematics and applied mathematics research.

Huijie Li
She is a student of Tianjin Agricultural University.


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