Performance Improvement of Plant Identification Model based on PSO Segmentation

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Author(s)

Heba F. Eid 1,*

1. Al-Azhar University, Faculty of Science, Cairo, Egypt

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2016.02.07

Received: 27 Apr. 2015 / Revised: 5 Sep. 2015 / Accepted: 16 Nov. 2015 / Published: 8 Feb. 2016

Index Terms

Plant identification, Segmentation, Particle Swarm Optimization, Information Gain, Discretization

Abstract

Plant identification has been a challenging task for many researchers. Several researches proposed various techniques for plant identification based on leaves shape. However, image segmentation is an essential and critical part of analyzing the leaves images. This paper, proposed an efficient plant species identification model using the digital images of leaves. The proposed identification model adopts the particle swarm optimization for leaves images segmentation. Then, feature selection process using information gain and discritization process are applied to the segmented image’s features. The proposed model was evaluated on the Flavia dataset. Experimental results on different kind of classifiers show an improvement in the identification accuracy up to 98.7%.

Cite This Paper

Heba F. Eid, "Performance Improvement of Plant Identification Model based on PSO Segmentation", International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.2, pp.53-58, 2016. DOI:10.5815/ijisa.2016.02.07

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