This is the description of the task that i am working on
first procedure (image processing)
1st step: Pre-process the Images
Convert images to grayscale to simplify the analysis.
Apply filters to reduce noise.
Perform thresholding to create a binary image where holes are distinguishable from the background.
2nd step: Detect Holes
Use contour detection to find holes in the binary image.
For closely situated holes, apply morphological operations or the watershed algorithm to separate
connected holes.
3rd step: Measure Holes
Approximate each detected contour to the closest circle or ellipse to determine the center and
radius/diameter.
Calculate the area of each hole using the radius or ellipse parameters.
4th Step: Calculate Distribution
Compute the distribution of holes across the image (e.g., hole area as a percentage of total area).
Perform spatial analysis to assess the clustering of holes.
5th Step: Data Visualization
Use Matplotlib or Seaborn to create histograms, scatter plots, and heatmaps of the distribution,
number, and size of holes