Economics at your fingertips  

Estimating Morphological Features of Plant Growth Using Machine Vision

Himanshu Gupta and Roop Pahuja
Additional contact information
Himanshu Gupta: National institute of Technology Jalandhar, Jalandhar, India
Roop Pahuja: National Institute of Technology Jalandhar, Jalandhar, India

International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2019, vol. 10, issue 3, 30-53

Abstract: Motivated by the fact that human visionary intelligence plays a vital role in guiding many of the agriculture practices, this article represents an effective use of machine vision technology for estimating plant morphological features to ascertain its growth and health conditions. An alternative to traditional, manual and time-consuming testing methods of plant growth parameters, a novel online plant vision system is proposed and developed on the platform of virtual instrumentation. Deployed in real time, the system acquires plant images using digital camera and communicates the raw image to host PC on Wi-Fi network. The dedicated application software with plant user interface, effective image processing and analysis algorithms, loads the plant images, extracts and estimates certain morphological features of the plant such as plant height, leaf area, detection of flower onset and fall foliage. The system was tested and validated under real-time conditions using different plants and leaves. Further, the performance of the system was statistically analysed to show promising results.

Date: 2019
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link) ... 18/IJAEIS.2019070103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

International Journal of Agricultural and Environmental Information Systems (IJAEIS) is currently edited by Frederic Andres

More articles in International Journal of Agricultural and Environmental Information Systems (IJAEIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

Page updated 2021-03-13
Handle: RePEc:igg:jaeis0:v:10:y:2019:i:3:p:30-53