System and method for quantifying a degree of fibrillation of fibers within pulp using image processing

A system for determining a degree of fibrillation within pulp using image processing, the system comprising:

• a memory;
• and
• one or more processors communicatively coupled to the memory, the one or more processors configured to:
• receive image data indicating an image of pulp;
• divide the image into a plurality of sub-images;
• perform size and shape analysis on the image to determine a fiber area of fibers within the image by performing adaptive thresholding on the image;
• perform edge detection on the plurality of sub-images to determine a count of edges of fibrils within the image;
• perform morphological image processing on the plurality of sub-images to determine a sum of grey levels associated with the fibrils within the image;
• calculate a degree of fibrillation associated with the pulp based at least in part on the fiber area, the count of edges of the fibrils, and the sum of grey levels associated with the fibrils by:
• calculating a first degree of fibrillation based on the fiber area and the count of edges of the fibrils;
• calculating a second degree of fibrillation based on the fiber area and the sum of grey levels associated with the fibrils;
• and
• calculating the degree of fibrillation based on a weighted average of the first degree of fibrillation and the second degree of fibrillation;
• and
• initiate display of an output that indicates the degree of fibrillation.

A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations for determining a degree of fibrillation within pulp using image processing, the operations comprising:

• receiving image data indicating an image of pulp;
• dividing the image into a plurality of sub-images;
• performing size and shape analysis on the image to determine a fiber area of fibers within the image by performing adaptive thresholding on the image;
• performing edge detection on the plurality of sub-images to determine a count of edges of fibrils within the image;
• performing morphological image processing on the plurality of sub-images to determine a sum of grey levels associated with the fibrils within the image;
• calculating a degree of fibrillation associated with the pulp based at least in part on the fiber area, the count of edges of the fibrils, and the sum of grey levels associated with the fibrils by:
• calculating a first degree of fibrillation based on the fiber area and the count of edges of the fibrils;
• calculating a second degree of fibrillation based on the fiber area and the sum of grey levels associated with the fibrils;
• and
• calculating the degree of fibrillation based on a weighted average of the first degree of fibrillation and the second degree of fibrillation;
• and
• initiating display of an output that indicates the degree of fibrillation.