Rice Leaf Blast Detection using on-Field Image of Western tract of Odisha based on Image Processing
Prabira Kumar Sethy1, Soubhagya Lina Dash2, Nalini Kanta Barpanda3, Amiya Kumar Rath4
1Prabira Kumar Sethy, Assistant Professor, Department of Electronics, Sambalpur University, Odisha.
2Soubhagya Lina Dash, M.Tech, Department of Electronics and Communication Engineering, Sambalpur University Institute of Information Technology, Odisha.
3Dr. Nalini Kanta Barpanda, Department of Electronics, Sambalpur University, Odisha.
4Prof. Amiya Kumar Rath, Professor, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 April 2019 | PP: 483-487 | Volume-8 Issue-6S April 2019 | Retrieval Number: F61000486S19/19©BEIESP
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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: Rice covers about 69% of the cultivated area and is the major crop, covering about 63% of the total area under food grains. It is the staple food of almost the entire population of Odisha; therefore, the state economy is directly linked with improvements in production and productivity of rice in the state. The main barrier of production of rice in this region is the rice leaf blast (RLB). So monitoring of RLB is necessary time to time. This paper presents a novel segmentation method to detect RLB using on-field image, which is combination of channel extraction, thresholding and masking.
Keywords: Rice Leaf Blast Detection, Image Processing Technique, Image Segmentation.
Scope of the Article: Communication