Image processing-based intelligent robotic system for assistance of agricultural crops
by Nikhil Paliwal; Pankhuri Vanjani; Jing-Wei Liu; Sandeep Saini; Abhishek Sharma
International Journal of Social and Humanistic Computing (IJSHC), Vol. 3, No. 2, 2019

Abstract: Agriculture has been practiced in conventional ways for centuries and supported with mechanical systems in the last few decades. With the evolution of robotic equipment and sensors, the researchers are focusing on introducing smart farming. In this paper, we propose improved algorithms for infection detection in leaves and field classification targeting a heterogeneous robotic system. Image processing methods have been used on the leaves of the plants to calculate the infection percentage in crops and elementary machine learning algorithm k-means clustering for classifying the field. Classification of the agricultural field has been done for growing different types of crops in a mixed cropping technique which has an advantage over other farming procedures. Early detection of diseases can help in better preventive measures in the early stages. We have used 3,150 images of crop diseases for three different types of crops and by smartly incorporating some previously established techniques. The primary objective of this paper includes the qualitative analysis of infection detection algorithms and further elaboration for the possible application of the suggested work in smart farming.

Online publication date: Tue, 13-Aug-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Social and Humanistic Computing (IJSHC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email