Automated Damaged Ginkgo Leaf Detection.

Abstract

The cram of plant disease refers to the studies of visually observable patterns of a particular plant. Nowadays produces face many traits/diseases. Damage of the insect is one of the most important trait/disease. Insecticides are not always proved efficient because insecticides may be toxic to some kind of birds. This paper introduces defect identification on Ginkgo leaves during production. This frame work introduces an active learning strategy through a set of passively trained leaf parameters. Under the supervision the trained parameters and input image are compared to know the characteristics of the leaves This algorithm is been used for identification of defective leaves using image processing techniques and for the removal of defective leaves through real time techniques.