OpenCV : Detecting bounding-box covering the label

Question

I have similar images with similar kind of background noise. Using OpenCV, is there a way to detect the area (detect contours) of the area covering the label. Or at least , is it possible to detect "rough" bounding-box covering the label area?

Answer 1

I've tried to accomplish this task, main issue which probably won't allow to generalize this algorithm is how to choose proper contour. I have two values(contour lengths) 3108 and 2855. You may try to fetch all you photos(if they on similar distance from camera) and set threshold for desired contour between 3050 and 2750, but no guaranty that it will work. So this is how i remove background(full code):

import cv2 
import numpy as np


image=cv2.imread('C:/Users/srlatch/Desktop/of8cA.png')
img = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)

def clear_vertical(img, target):
    for i in range(img.shape[1]):
        for j in range(img.shape[0]):
            if img[j][i]:
                break
            else:
                target[j][i]=[0,0,0]

def clear_horizontal(img, target):
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            if img[i][j]:
                break
            else:
                target[i][j]=[0,0,0]



def turn_off(img):
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            img[i][j]=0

def turn_on(img,result):
    for i in result:
       img[i[0][1]][i[0][0]]=255


def f(list):
    max=[]
    for i in list:
        if len(i)>len(max):
            max=i
    return max 

def rem(ls, thresh):
    new_c=[]
    for i in ls:
        if len(i)>thresh:
            new_c.append(i)
    return new_c 

def rn(ls,min,max):
    ret=[]
    for i in ls:
         if len(i)<max and len(i)>min:
             print(len(i))
             ret.append(i)
    return ret

#ret,tresh = cv2.threshold(img,40,255,cv2.THRESH_BINARY)
kernel = np.ones((2,2),np.uint8)
new=cv2.Canny(img,190,1)
dilated=cv2.dilate(new, kernel)
tresh,c,hr=cv2.findContours(dilated,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
c=rn(c, 2600, 4000)
turn_off(new)
turn_on(new,c[0])

clear_horizontal(new,image)
clear_vertical(new,image)

cv2.imwrite('result_image_end.png',image)

cv2.imshow('wnd',image)
cv2.waitKey(100)

I've tried different approaches, but this seems to work better than the others. I believe in opencv exist function which can substitute this clear_horizontally and vertically, but i can't remember it name. Hope it helps!