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I want to extract the red conjunctiva region using OpenCV (python) and store it as ROI(Region of Interest):

The final image should show only the red region. Using mask and getting the red region does not work always. A more generalized code is required.

Edit: Right now I am able to save the region of the eye containing the conjunctiva region.

Now I need to detect the red area from the 2nd image. That region is my ROI. However, I need to make sure that the code developed should be able to detect such a region always.

My code till now (in Python) is as follows:

import cv2
import numpy as np

def hisEqulColor(img):
    ycrcb=cv2.cvtColor(img,cv2.COLOR_BGR2YCR_CB)
    channels=cv2.split(ycrcb)
    #print (len(channels))
    cv2.equalizeHist(channels[0],channels[0])
    cv2.merge(channels,ycrcb)
    cv2.cvtColor(ycrcb,cv2.COLOR_YCR_CB2BGR,img)
    return img


def reduce_size_of_image(img):
    height, width = img.shape[:2]
    eyebrow_h = int(height / 1.6)   ## Can be made ~25% 
    width_left = int(width / 6)
    width_right = int(width / 6)
    # img = img[eyebrow_h:height, 0:width]  # cut eyebrows out (15 px)
    img = img[eyebrow_h:height, width_left:(width - width_right)]
    return img


img = cv2.imread("Test_Image_21.jpeg")
eyesCascade = cv2.CascadeClassifier("haarcascade_eye.xml")
eyes = eyesCascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(100, 100))

if len(eyes) != 0:
    print("Number of Eyes detected = ", len(eyes))
    for (x, y, w, h) in eyes:
        eye = img[y:y + h, x:x + w]
        ROI = eye
        cv2.imwrite("ROI_1.jpg", ROI)

        ROI_reduced = cv2.imread('ROI_1.jpg')
        ROI_reduced = reduce_size_of_image(ROI_reduced)

        cv2.imshow('ROI', ROI)
        cv2.waitKey(0)
        cv2.imshow('ROI Reduced', ROI_reduced)
        cv2.waitKey(0)
        cv2.imwrite("ROI_Reduced.jpg", ROI_reduced)


        ROI_reduced_1 = cv2.imread('ROI_Reduced.jpg')
        ROI_reduced_1 = cv2.cvtColor(ROI_reduced_1, cv2.COLOR_BGR2GRAY)

        CAN'T CANNOT PROCEED FROM HERE ONWARDS!!
        #ret,thresh1 = cv2.threshold(ROI_reduced_1,140,255,cv2.THRESH_BINARY_INV)
        #kernel = np.ones((3,3),np.uint8)
        #opening = cv2.morphologyEx(thresh1, cv2.MORPH_CROSS, kernel)
        #closing = cv2.morphologyEx(thresh1, cv2.MORPH_CLOSE, kernel)
        #ROI_reduced_1 = cv2.cvtColor(ROI_reduced_1, cv2.COLOR_BGR2GRAY)
        #edges = cv2.Canny(ROI_reduced_1, 100, 200)

        #threshold = 80
        #_, img_thresh = cv2.threshold(ROI_reduced_1, threshold, 255, cv2.THRESH_BINARY)


        #cv2.imshow('ROI Reduced after histogram equalization', img_thresh)
        #cv2.waitKey(0)

else:
    print("\nNo eyes detected!!")

cv2.destroyAllWindows()