When the difference is the lowest, the index indicates the value of the threshold tĭiff = # using cumulative histogram and comparing it to a target value by calculating the difference. P0 = (z1 - m1) / pd # p0 should be the percentage of the pixels to which the value 0 is attributed The name of the further variables stems from the paper. #from the paper, calculating the 4 first odrers m0, m1, m2, m3 to get to p0. Pix_sum = B.shape*B.shape # calculating the sum of the pixels H, S, B = cv2.split(img) # spliting the image into HSBī_histo = (B) # making the histogram Hsv_img = cv2.cvtColor(filt_img, cv2.COLOR_RGB2HSV)
IMAGEJ AUTO THRESHOLD CODE
As I couldn't find any help or piece of code on the subject, here I am.įrom the paper "moment-preserving thresholding: a new approach, Tsai" ( here), I did this: import numpy as np On Python, I wish to have the value of the threshold t from which the segmentation is done. In Image J, I split the image into HSB, then use the Moments Auto-threshold on the B channel. I would like to transfer my image processing from Image J (Fiji) to Python.
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