Image processing algorithm to estimate ice-plant leaf area from RGB images under different light conditions

The productivity of horticultural crops in an artificial light condition are highly influenced by the structure of plant and the area coverage. Accurate measurement of leaf area is very important for predicting plant water demand and optimal growth. In this paper, we proposed an image processing alg...

Full description

Saved in:
Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2021-11, Vol.924 (1), p.12013
Main Authors: Islam, S, Reza, M N, Chowdhury, M, Islam, M N, Ali, M, Kiraga, S, Chung, S O
Format: Article
Language:English
Subjects:
Algorithms
Color imagery
Digital cameras
Digital imaging
Gray scale
Horticultural crops
Image classification
Image processing
Leaf area
Leaves
Light sources
Pixels
Plant growth
Plants
R&D
Research & development
Water demand
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The productivity of horticultural crops in an artificial light condition are highly influenced by the structure of plant and the area coverage. Accurate measurement of leaf area is very important for predicting plant water demand and optimal growth. In this paper, we proposed an image processing algorithm to estimate the ice-plant leaf area from the RGB images under the artificial light condition. The images were taken using a digital camera and the RGB images were transformed to grayscale images. A binary masking was applied from a grayscale image by classifying each pixel, belonging to the region of interest from the background. Then the masked images were segmented and the leaf region was filled using region filling technique. Finally, the leaf area was calculated from the number of pixel and using known object area. The experiment was carried out in three different light conditions with same plant variety (Ice-plant, Mesembryanthemum crystallinum) . The results showed that the correlation between the actual and measured leaf area was found over 0.97 (R 2 :0.973) by our proposed method. Different light condition also showed significant impact on plant growth. Our results inspired further research and development of algorithms for the specific applications.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/924/1/012013