python - Floor Plan Edge Detection - Image Processing?

Question

I am a guy from a completely different discipline who need some Image Processing techniques to achieve this goal in a project. I need to derive the edges from an indoor floor plan, as shown below

I have tried this particular Python edge detect snippet:

from PIL import Image, ImageFilter

image = Image.open('L12-ST.jpg')
image = image.filter(ImageFilter.FIND_EDGES)
image.save('new_name.png') 

However, it is returning too much more details than I need. It basically detects all the edges including the room walls. Actaully, what I need are just the corridor walls. So I expect something like this

How may I do this? I am using Python, but any generic or general pointers or even some keywords are very much appreciated.

Answer 1

here's an example. you will need to have opencv package to run it.

there's a break there because the image has artifacts. if you use a higher quality image, it's probably going to be better. if you cant have a higher quality image, may be morphological operations can be used to connect the small gaps and remove quarter circle protrusions.

import cv2
import numpy as np

img = cv2.imread('c:/data/floor.jpg')
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
gray=255-gray

contours,hierarchy = cv2.findContours(gray,cv2.RETR_LIST ,cv2.CHAIN_APPROX_NONE )

for cnt in contours:
    area = cv2.contourArea(cnt)
    if area>9000 and area<40000:
        cv2.drawContours(img,[cnt],0,(255,0,0),2)

cv2.imshow('img',img)
cv2.waitKey()

edit

did some preprocessing to fix the break

import cv2
import numpy as np

img = cv2.imread('c:/data/floor.jpg')

img=cv2.resize(img,(1700,700))
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
gray=255-gray
gray=cv2.threshold(gray,4,255,cv2.THRESH_BINARY)[1]
gray=cv2.blur(gray,(15,1))
contours,hierarchy = cv2.findContours(gray,cv2.RETR_LIST ,cv2.CHAIN_APPROX_NONE )

for cnt in contours:
    area = cv2.contourArea(cnt)
    if area>150000 and area<500000:
        cv2.drawContours(img,[cnt],0,(255,0,0),2)

cv2.imshow('img',img)
cv2.waitKey()