How to detect a specific inner rectangle in a complex shape

Question

I have the following input image:

and I do like to crop the inner max rectangle like this (Expected Output):

but when I do contour detection I get the external rectangle (Current Result):

import cv2
import numpy as np

res = cv2.imread("input.png", 0)

k0 = 5
dgauss = cv2.GaussianBlur(res, (k0, k0), 0)

op = cv2.MORPH_CLOSE
morph_elem = cv2.MORPH_RECT
morph_size = 51
element = cv2.getStructuringElement(morph_elem, (2*morph_size + 1, 2*morph_size+1), (morph_size, morph_size))
mph = cv2.morphologyEx(dgauss, op, element)

contours = cv2.findContours(mph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[0]

c_th = 10000

for idx, cnt in enumerate(contours):
    if(cv2.contourArea(cnt)>c_th):
        x,y,w,h = cv2.boundingRect(cnt)
        print(x,y,w,h)
        cv2.rectangle(res,(x,y),(x+w,y+h),128,1)

cv2.imshow("final", res)
cv2.waitKey(0)

Can you please tell me how can I get the inner rectangle without hard-coding the contour coordinates (x, y, w, h)? thanks in advance.

Answer 1

I have solved this issue by:

1. Aligning depth to the color.
2. Segmenting the green table using HSV information as explained here
3. Cropped the desired rectangle (ROI) using color information.