Open AccessLeaf Disease Classification using Advanced SVM Algorithm
Author(s) -
Rima Herlina Siburian,
Rahmi Karolina,
Phong Thanh Nguyen,
E. Laxmi Lydia,
K. Shankar
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1138.0886s19
Subject(s) - pest analysis , focus (optics) , pesticide , support vector machine , computer science , segmentation , crop , artificial intelligence , agricultural engineering , stage (stratigraphy) , machine learning , agronomy , engineering , biology , horticulture , physics , optics , paleontology
Presently there are many alternates of pesticides and unfortunately a very big portion of the industry is relies and using such poisons to protects crops to prevent from bugs attack and spreading of infection. Such pesticides are seriously very harmful and used unorganic chemicals. Even some of such pesticides are beneficial for insects too. Even some times there is also an possibility that such chemicals may be automatically washed during rain or watering the crops. So the research since years on green house agro system focus on early pest detection. Such methodology focus on observing plants by camera. The images captured by cameras can be used to analyzed that weather the plants are infected or not. A number of methods and algorithms such as color conversion, segmentation, k-mean, knn etc are used to classified such images. This research is focusing on the interpretation of image for early stage pest detection so that the crop should be prevented from damage.