Planshot

dc.contributor.advisor	Natsheh, Abdel-Razzak
dc.contributor.author	sha'ar, Lamees
dc.contributor.author	Attallah, Motaz
dc.contributor.author	Jammal, Ahamad
dc.date.accessioned	2017-10-23T07:27:58Z
dc.date.available	2017-10-23T07:27:58Z
dc.date.issued	2017
dc.description.abstract	The artificial intelligence technique for automatic detection and classification is very important factor to prevent disease outbreaks. By using image processing techniques. Most plant disease are caused by Fungi, bacteria and viruses. Our concentration about viruses ,especially Tomato mosaic and Tomato Yellow Leaf Curl Viruses. They are extremely tiny particles consisting of protein and genetic material with no associated protein. The developed processing scheme consists images of the infected Tomato leaves that are captured by mobile camera, those images are preprocessed using image histogram equalization, filtering, color transformation and segmentation techniques to detect infected part of the leaves. Then the infected leaf has been used for the classification purpose using Decision Trees classifier. Our demo works as follows : The user takes a picture of the infected tomato leave, then this image is uploaded to the server and a series of operations are carried out. At the end, the result of the infected leave with specific virus is returned with a protective method.	en_US
dc.identifier.uri	https://hdl.handle.net/20.500.11888/10455
dc.language.iso	en_US	en_US
dc.title	Planshot	en_US
dc.type	Graduation Project	en_US

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