I want to straighten the hand in the image based on the middle finger. I have about 10000 of these hand X-ray images to preprocess. The preprocess I did so far:

1. Apply Gaussian Blur and Threshold (Binary Otsu) on the image.
2. Apply dilation to get a single object (in this case a hand).
3. Used cv2.findContours() to draw outline along the edges around the hand.
4. Apply cv2.convexHull() and then cv2.convexityDefects() to mark the points that are farthest away from the convex hull. To filter out the ones of interest between the fingers, I only considered those that are more than a certain distance from the convex hull.

The code below describes the above-mentioned:

import cv2
import numpy as np
from matplotlib import pyplot as plt

img_path = "sample_image.png"

# Getting the threshold of the image:
image = cv2.imread("sample_image.png")
original = image.copy() 
blank = np.zeros(image.shape[:2], dtype = np.uint8)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (127,127), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY   cv2.THRESH_OTSU)[1]

# Merge into a single contour
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
dilate = cv2.dilate(thresh, kernel, iterations = 2)

# Drawing the contours along the edges of the hand in X-ray:
contours, hierarchy = cv2.findContours(dilate, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours = max(contours, key = lambda x: cv2.contourArea(x))

cv2.drawContours(image, [contours], -1, (255,255,0), 2)

# To mark the points that are farthest away from the convex hull, one for each "convexity defect"
hull = cv2.convexHull(contours, returnPoints = False)
defects = cv2.convexityDefects(contours, hull)
for i in range(defects.shape[0]):
    _, _, farthest_point_index, distance = defects[i, 0]
    farthest_point = contours[farthest_point_index][0]
    if distance > 50_000:
        circle = cv2.circle(image, farthest_point, 20, [0,0,255], -1)

• Input image =

  Note that you can barely see the ellipse here, so I plotted the ellipse's longest axis using cv2.line(image, (x1, y1), (x2, y2),(255,0,255),4).

  STEP2: Rotating the image:

  Following

  I would be curious to know how this script performs on the remainder of your data.