I am trying to get diameters on different points of an object over a certain length using computer vision to replace the use of optical micrometer (which also measures diameter using optic principle).

Image of a yarn:

How can I calculate the diameter of this object (textile yarn) on multiple points (red lines) along its length as shown in the image using OpenCV python?

CodePudding user response：

An OpenCV solution. The main idea is to:

1. Detect edges
2. Find the contours of the edges
3. Fill in the contour areas
4. Go through each column in the image and count the nonzero pixels

1., 2. and 3. could possibly be simplified by a single thresholding step depending on your use case

import numpy as np 
import cv2


src = cv2.imread('/path/to/src.jpg')
mask = np.zeros(src.shape, dtype=np.uint8)
w, h, c = src.shape

# edge detection
threshold = 100
gray = cv2.Canny(src, threshold, threshold * 2)

cv2.imshow('', gray)
cv2.waitKey(0)

# find contours
cnts = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
threshold_area = 0.5

# fill area withing contours with white color
for c in cnts:
    area = cv2.contourArea(c)
    if area > threshold_area:
        cv2.drawContours(mask, [c], -1, (255, 255, 255), -1)

cv2.imshow('', mask)
cv2.waitKey(0)

# get non zero values (height) of each column
column_pixels = [cv2.countNonZero(mask[:, i]) for i in range(0, w)]
print(column_pixels)

Src image:

Canny result:

After filling in contours with white color:

countNonZero is applied on this last image for each column