Computer Vision in Smart Agriculture and Crop Management

4Stereo Vision Subsystem and Scene Segmentation Self-Steering Tractors in Smart Agriculture

Dileep Pulugu^1*, Revathy Pulugu², K. Muthumanickam³, S. Gopinath⁴ and A. Manikandan⁵

¹CSE, Malla Reddy College of Engineering and Technology, Hyderabad, India

²CSE, Narsimha Reddy Engineering College, Kompally, Hyderabad, Telangana State, India

³Information Technology, Kongunadu College of Engineering and Technology, Thottiam, Tamil Nadu, India

⁴ECE, Karpagam Institute of Technology, Coimbatore, India

⁵ECE, SRM Institute of Science and Technology (Deemed to be University), Kattankulathur, Chennai, India

Abstract

A key component of smart agriculture is the automatic navigation of agricultural equipment. Machine vision algorithms are being used more and more in smart agricultural machinery applications to pinpoint the precise position of crop rows and plan vehicle navigation routes in real time. This problem describes a tractor system based on vision. This research focuses more precisely on the system design, user safety, typical navigational mistakes, tractor navigation control systems, and presentation. Current research has demonstrated that stereo vision systems offer stronger control stability and are more effective at real-time on-site navigation than monocular systems. It is very accurate for many different crops, such as cotton, sunflower, and corn. By combining backdrops of foliage and sky, it is able to successfully derive orchard navigation pathways. This article offers a quick ...