Study of Plant Phenotype using Image Segmentation Techniques
DOI:
https://doi.org/10.26438/ijcse/v8i5.2330Keywords:
Segmentation, Phenotype, Sobel operator, PlantCV platform, Shoot module,, Root module, SegmentationEdge Detection, threshold Segmentatio, , Gaussian Blur, Median Blur, Region of Interest(ROI)Abstract
The study of plant phenotype using segmentation techniques is one the leading research area in the field of agricultural technology. Plant phenotype is a technical term which is used to describe the observable characteristics of the plant like width, height, biomass, plant, leaf shape and so on. It is required in order to study about the physical characteristics of the plant like finding the area, height, width, structure of the plant and skeleton generation of the plant root etc. It is used in the field of agricultural technology to carry out various types of research. This paper explores the use of different segmentation methods in order to get efficient segmented images for the plant's shoot and root systems. The segmentation methods used are threshold segmentation, edge detection, and followed by contour segmentation on PlantCV platform. The proposed work partitions the segmentation process in four steps, where the output of each step is given as input to the next step. We use the thresholding method as a first step in plant image segmentation process to remove the background and noise in the image. This step is followed by edge detection method to remove the unwanted regions and to detect false edges in a segmented plant image. Next, the contour segmentation is used to identify the complete structure of the plant. Then from the output image obtained, features are extracted in JSON format and the segmented images acquired are stored in an output folder.
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