Recognition of Leaf Images Based on generic fourier descriptor Using SVM

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DC Field	Value	Language
dc.contributor.author	ABAIDI, Abedelkader
dc.contributor.author	Aymen, Mohamed
dc.contributor.author	Kohili, Mohammed / Supervisor
dc.date.accessioned	2019-06-10T18:37:36Z
dc.date.available	2019-06-10T18:37:36Z
dc.date.issued	2018
dc.identifier.uri	http://www.univ-adrar.dz/:8080/xmlui/handle/123456789/1506
dc.description	Computer Science	en_US
dc.description.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.	en_US
dc.language.iso	en	en_US
dc.publisher	Ahmed Draia University - Adrar	en_US
dc.subject	SVM multiclass	en_US
dc.subject	Generic Fourier Discriptor GFD	en_US
dc.subject	Recognition	en_US
dc.subject	leaves	en_US
dc.subject	Support Vector machine SVM	en_US
dc.subject	Intelligent Systems	en_US
dc.title	Recognition of Leaf Images Based on generic fourier descriptor Using SVM	en_US
dc.type	Thesis	en_US
Appears in Collections:	Mémoires de Master

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