Image Processing Techniques Aiding Smart Agriculture

Author:

Tripathy Aspira S.1,Sharma Deepak Kumar1ORCID

Affiliation:

1. Netaji Subhas University of Technology, India

Abstract

With the ever-increasing load of satiating the agricultural demands, the transition of the orthodox methods into smart ones is inevitable. The agriculture sector for long has served as a momentous source of livelihood for many globally. It is arguably a major topic for nations of the development spectrum, contributing towards their export earnings and aiding in their GDP assessment. Thus, it is quite conspicuous that nations would work towards its expansion. In congruence, the burgeoning population and its demands have posed a threat to the environment due to extensive exploitation of resources, which in turn is escalating towards the downfall of the quality and quantity of agricultural produces requiring a 70% increment in the produces by 2050 for sustainability. To combat such hurdles, developed techniques are being employed. Through a survey of existing literature, this chapter provides a comprehensive overview of various image processing means that could come in handy for ameliorating the present scenario and shows their implied extension in the smart farming world.

Publisher

IGI Global

Reference76 articles.

1. Astonkar, S. R., & Shandilya, V. K. (2018). Detection and analysis of plant diseases using image processing technique. International Research Journal of Engineering and Technology (IRJET), 05(04), 4. Retrieved from https://www.irjet.net/archives/V5/i4/IRJET-V5I4717.pdf

2. Avendano, J., Ramos, P. J., & Prieto, F. A. (2017). A system for classifying vegetative structures on coffee branches based on videos recorded in the field by a mobile device. Expert Systems with Applications, 88, 178e192.

3. Using Digital Image Processing for Counting Whiteflies on Soybean Leaves.;J.Barbedo;Journal of Asia-Pacific Entomology,2014

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