Extract bounding box and save it as an image

Suppose you have the following image:

Now I want to extract each of the independent letters into individual images. Currently, I've recovered the contours and then drew a bounding box, in this case for the character a:

After this, I want to extract each of the boxes (in this case for the letter a) and save it to an image file.

Expected result:

Here's my code so far:

import numpy as np import cv2 im = cv2.imread('abcd.png') im[im == 255] = 1 im[im == 0] = 255 im[im == 1] = 0 im2 = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY) ret,thresh = cv2.threshold(im2,127,255,0) contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) for i in range(0, len(contours)): if (i % 2 == 0): cnt = contours[i] #mask = np.zeros(im2.shape,np.uint8) #cv2.drawContours(mask,[cnt],0,255,-1) x,y,w,h = cv2.boundingRect(cnt) cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2) cv2.imshow('Features', im) cv2.imwrite(str(i)+'.png', im) cv2.destroyAllWindows() 

Thanks in advance.

3 Answers

The following will give you a single letter

letter = im[y:y+h,x:x+w] 

Here's an approach:

• Convert image to grayscale
• Otsu's threshold to obtain a binary image
• Find contours
• Iterate through contours and extract ROI using Numpy slicing

After finding contours, we use cv2.boundingRect() to obtain the bounding rectangle coordinates for each letter.

x,y,w,h = cv2.boundingRect(c) 

To extract the ROI, we use Numpy slicing

ROI = image[y:y+h, x:x+w] 

Since we have the bounding rectangle coordinates, we can draw the green bounding boxes

cv2.rectangle(copy,(x,y),(x+w,y+h),(36,255,12),2) 

Here's the detected letters

Here's each saved letter ROI

import cv2 image = cv2.imread('1.png') copy = image.copy() gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) thresh = cv2.threshold(gray,0,255,cv2.THRESH_OTSU + cv2.THRESH_BINARY)[1] cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cnts = cnts[0] if len(cnts) == 2 else cnts[1] ROI_number = 0 for c in cnts: x,y,w,h = cv2.boundingRect(c) ROI = image[y:y+h, x:x+w] cv2.imwrite('ROI_{}.png'.format(ROI_number), ROI) cv2.rectangle(copy,(x,y),(x+w,y+h),(36,255,12),2) ROI_number += 1 cv2.imshow('thresh', thresh) cv2.imshow('copy', copy) cv2.waitKey() 

 def bounding_box_img(img,bbox): x_min, y_min, x_max, y_max = bbox bbox_obj = img[y_min:y_max, x_min:x_max] return bbox_obj img = cv2.imread("image.jpg") bounding_box_img(img,bbox) 

this returns cropped image (bounding box)

in this aproach, bounding box coordinates bases on pascal-voc annotation formats like here