A new threshold segmentation method for cotton root images

doi:10.3969/j.issn.1000-1565.2022.02.003

Abstract

Abstract: In order to detect the cotton root in situ, an automatic global threshold segmentation method was proposed for cotton root image segmentation. Digital device imaging method was used to collect the cotton in-situ root system images, and the automatic global threshold method was used to segment the images. Firstly, the acquired root images are spatially transformed, and the acquired root images are segmented in HSV space. Then, the global threshold segmentation method is used to select the threshold value to binarize the image, and the closed operation method is used to denoise the binary image. Finally, all the noises in the image were filtered through the shape feature screening, and the slender root features in the image are selected. This algorithm can effectively suppress the influence of noise and soil impurities, and can accurately segment the root system. It is an effective method for fast detection of crop root images.

Key words: root phenotype, threshold segmentation, nondestructive testing

CLC Number:

TP391

SHE Lixuan, KANG Jia, WANG Nan, SHAO Limin. A new threshold segmentation method for cotton root images[J]. Journal of Hebei University(Natural Science Edition), 2022, 42(2): 124-130.

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