X-ray CT image analysis for morphology of muskmelon seed in relation to germination

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Internal morphological damage can have critical effects on the development and germination power of seeds. This study investigates the morphological characteristics of naturally aged muskmelon seed in relation to germination ability. An X-ray microCT scanner was employed to generate CT images and then several image processing techniques such as re-slicing, contrast enhancement, noise reduction, and segmentation were performed on the images. Afterwards, fifteen preprocessed images were nominated from each sample, and features of interest (i.e., local binary pattern, Gabor, local Fourier (FFT), texture, contrast and Haralick textural (Tx) features) were extracted. The sequential forward selection (SFS) method was applied as a search strategy to identify the most relevant features using a variety of different objective functions. It was determined that the Fisher discriminant objective function performed the best. A germination test was performed to evaluate the seed viability and the information was used to construct the training and validation data set. The seeds were divided into 2 groups: viable (group-1) and non-viable (group-0). Different classifiers were probed to determine the optimal performer, where the linear discriminant classifier resulted in an accuracy of 98.9%, with 10-fold cross-validation using eighteen selected features. The findings of this study indicate that CT imaging is a potential tool for the classification of seeds based on the characterisation of internal morphologically.