Leaf Disease Classification using Advanced SVM Algorithm
Rima Herlina S. Siburian1, Rahmi Karolina2, Phong Thanh Nguyen3, E. Laxmi Lydia4, K. Shankar5
1Rima Herlina S. Siburian, Universitas Papua, Indonesia.
2Rahmi Karolina, Universitas Sumatera Utara, Indonesia.
3Phong Thanh Nguyen, Department of Project Management, Ho Chi Minh City Open University, Vietnam.
4E.Laxmi Lydia, Vignan’s Department of Computer Science and Engineering, Institute of Information Technology (A), Visakhapatnam (A.P), India.
5K.Shankar, Department of Computer Applications, Alagappa University, India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 712-718 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F11380886S19/19©BEIESP | DOI: 10.35940/ijeat.F1138.0886S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Early PEST Detection, Segmentation Algorithm, Pesticides Alternates, Binary Image Conversion.
Scope of the Article: Classification