Performance Improvement of Plant Identification Model based on PSO Segmentation
Автор: Heba F. Eid
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 2 vol.8, 2016 года.
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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%.
Plant identification, Segmentation, Particle Swarm Optimization, Information Gain, Discretization
Короткий адрес: https://sciup.org/15010796
IDR: 15010796
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