0000000000375625
AUTHOR
Vahid Mohammadi
A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images
Abstract In precision agriculture, the accurate segmentation of crops and weeds in agronomic images has always been the center of attention. Many methods have been proposed but still the clean and sharp segmentation of crops and weeds is a challenging issue for the images with a high presence of weeds. This work proposes a segmentation method based on the combination of semantic segmentation and K-means algorithms for the segmentation of crops and weeds in color images. Agronomic images of two different databases were used for the segmentation algorithms. Using the thresholding technique, everything except plants was removed from the images. Afterward, semantic segmentation was applied usin…
Design, Development and Evaluation of a System for the Detection of Aerial Parts and Measurement of Growth Indices of Bell Pepper Plant Based on Stereo and Multispectral Imaging
During the growth of plants, monitoring them brings much benefits to the producers. This monitoring includes the measurement of physical properties, counting plants leaves, detection of plants and separation of them from weeds. All these can be done different techniques, however, the techniques are favorable that are non-destructive because plant is a very sensitive creature that any manipulation can put disorder in its growth or lead to losing leaves or branches. Imaging techniques are of the best solutions for plants growth monitoring and geometric measurements. In this regard, in this project the use of stereo imaging and multispectral data was studied. Active and passive stereo imaging …
Estimation of Leaf Area in Bell Pepper Plant using Image Processing techniques and Artificial Neural Networks
Measurement and estimation of physical properties of plant leaves have always been considered as important requirements for monitoring and optimizing of plant growth. This study aimed at utilization of image processing and artificial intelligence techniques for non-invasive and non-destructive estimation of bell pepper leaves properties in the first month of growth. Physical properties of bell pepper plant leaves were extracted from RGB images. The algorithm makes use of gradient magnitude and watershed image. Leaf area as the most important index of growth was estimated as a function of other physical parameters including leaf length, width, perimeter etc. Using stereo imaging, the leaf di…