Recognition of Leaf Images Based on generic fourier descriptor Using SVM

Please use this identifier to cite or link to this item: https://dspace.univ-adrar.edu.dz/jspui/handle/123456789/1506

Title:	Recognition of Leaf Images Based on generic fourier descriptor Using SVM
Authors:	ABAIDI, Abedelkader Aymen, Mohamed Kohili, Mohammed / Supervisor
Keywords:	SVM multiclass Generic Fourier Discriptor GFD Recognition leaves Support Vector machine SVM Intelligent Systems
Issue Date:	2018
Publisher:	Ahmed Draia University - Adrar
Abstract:	We present in this thesis an experimental study, which aims to do an optimal selection of SVM model for the recognition of leaves. Include the generic Fourier descriptor for features extraction and type of classification (one-against-all) the choice of these parameters has a great influence on the final performance of the classification and the computation time. This work required the realization of a complete system of recognition offline of leaves, the generation of database of 32 classes each class has more than 50 images, which is approximately 1907 images. Preliminary results are very encouraging and promising compared to the general literature survey.
Description:	Computer Science
URI:	http://www.univ-adrar.dz/:8080/xmlui/handle/123456789/1506
Appears in Collections:	Mémoires de Master

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