OpenCV MSER detect text areas - Python

Question

I have an invoice image, and I want to detect the text on it. So I plan to use 2 steps: first is to identify the text areas, and then using OCR to recognize the text.

I am using OpenCV 3.0 in python for that. I am able to identify the text(including some non text areas) but I further want to identify text boxes from the image(also excluding the non-text areas).

My input image is: and the output is: and I am using the below code for this:

img = cv2.imread('/home/mis/Text_Recognition/bill.jpg')
mser = cv2.MSER_create()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #Converting to GrayScale
gray_img = img.copy()

regions = mser.detectRegions(gray, None)
hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in regions]
cv2.polylines(gray_img, hulls, 1, (0, 0, 255), 2)
cv2.imwrite('/home/mis/Text_Recognition/amit.jpg', gray_img) #Saving

Now, I want to identify the text boxes, and remove/unidentify any non-text areas on the invoice. I am new to OpenCV and am a beginner in Python. I am able to find some examples in MATAB example and C++ example, but If I convert them to python, it will take a lot of time for me.

Is there any example with python using OpenCV, or can anyone help me with this?

Answer 1

Below is the code Import packages

import cv2
import numpy as np

#Create MSER object
mser = cv2.MSER_create()

#Your image path i-e receipt path
img = cv2.imread('/home/rafiullah/PycharmProjects/python-ocr-master/receipts/73.jpg')

#Convert to gray scale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

vis = img.copy()

#detect regions in gray scale image
regions, _ = mser.detectRegions(gray)

hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in regions]

cv2.polylines(vis, hulls, 1, (0, 255, 0))

cv2.imshow('img', vis)

cv2.waitKey(0)

mask = np.zeros((img.shape[0], img.shape[1], 1), dtype=np.uint8)

for contour in hulls:

    cv2.drawContours(mask, [contour], -1, (255, 255, 255), -1)

#this is used to find only text regions, remaining are ignored
text_only = cv2.bitwise_and(img, img, mask=mask)

cv2.imshow("text only", text_only)

cv2.waitKey(0)