Publication Type : Conference Proceedings
Publisher : 2017 4th International Conference on Advanced Computing and Communication Systems
Source : 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS) (2017)
Url : https://ieeexplore.ieee.org/document/8014724
Keywords : Arduino due, Cameras, Computer vision, image motion analysis, Image segmentation, Integrated optics, Noise model Keyframe, Optical flow, Optical imaging, Raspberry Pi, rice counting, Segmentation, Video analytics
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2017
Abstract : The traditional method of tea leaves harvesting is done in following ways, such as Hand Plucking using knife, Hand Plucking without using Knife. In the recent years the harvesting machines are introduced which can be operated by a single person or multiple persons and also a robotic vehicle. The challenges faced in the above systems are not enough capacity of human resources, intruding of wild animals into the fields, the machines don't have the intelligence on its own and also the robotic vehicle is terrain dependent which can be used only in the plain terrain. But the fields in India are irregular terrain. This paper proposed a semi-automatic system where the tea leaves will be harvested automatically by a robotic arm which will pluck the tea leaves based on the grade. The grade identification is done using the image processing techniques such as, Key Frame extraction, Rice counting, optical flow, and noise model with segmentation. The proposed work is novel because it has capabilities of considering motion with key frame capabilities and the noise model.
Cite this Research Publication : Dr. Senthil Kumar T. and Murthi, M., “A semi automated system for smart harvesting of tea leaves”, 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS). 2017.