Nature Inspired Algorithms as a Tool for Diseased Millets Leaf Segmentation
Pavithra P1, Aishwarya P2
1Pavithra P, Research scholar, Atria Institute of Technology, Bangalore, India.
2Dr. Aishwarya P, Professor, Department of CSE, Atria Institute of Technology, Bangalore, India.
Manuscript received on January 23, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 3557-3562 | Volume-9 Issue-3, February 2020. | Retrieval Number: C5706029320/2020©BEIESP | DOI: 10.35940/ijeat.C5706.029320
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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: Agriculture is the main occupation undertaken by majority of population in India. The Indian farmers produce food grains for entire population. Growing population needs constant increase in quantity and quality of agriculture produce. This is possible only by adopting improved technology in production and plant protection. Hence, technology intervention is at every stage of production and food processing is needed. Timely and suitable plant protection measures directly improve quantity and quality of agriculture produce. Effective result oriented plant protection mainly involves early detection of pest and diseases and suitable control measures. The entire human population consume products of food grains like cereals and millets as their staple food. This paper aims at summarizing common image processing methods to identify plant diseases and how it could be improved using nature inspired algorithm.
Keywords: Agriculture, Image Processing, Leaf diseases, Millets, Nature Inspired Algorithms.