classification of hemp fibers based on morphological features

In this workflow, you can use MorphoLibJ to generate accurate morphometric measurements

• First the fibers are segmented by mathematical morphology:
  • for example by using MorphoLibJ:
    • Create a marker image by creating a rough mask with extended regional maxima (similar to Find Max), such that you have one max per fiber
    • Use the marker controlled watershed (in MorpholLibJ/ Segmentation/ marker controlled watershed) : indicate the original grayscale image as the input, Marker will be your maxima image, select None for mask
    • it will create a label mask of your fibers
•  In MorphoLibJ /analyze/ select Region Morphometry: this will compute different shape factors which are more robust than the ones implemented by default in ImageJ
• Export the result table created to a csv file
• Then for example in Matlab or R, you can apply a PCA analysis (Principal component analysis) followed by a k-means with the number of class (clusters) (different fibers type) you want to separate.
• You can then add this class as a new feature to your csv file.
• From this you can sort your labelled fibers into these clusters for a visual feedback or further spatial analysis