Python + OpenCV: OCR Image Segmentation

Question

I am trying to do OCR from this toy example of Receipts. Using Python 2.7 and OpenCV 3.1.

Grayscale + Blur + External Edge Detection + Segmentation of each area

Answer 1

Preprocessing the image by converting the desired text in the foreground to black while turning unwanted background to white can help to improve OCR accuracy. In addition, removing the horizontal and vertical lines can improve results. Here's the preprocessed image after removing unwanted noise such as the horizontal/vertical lines. Note the removed border and table lines

import cv2

# Load in image, convert to grayscale, and threshold
image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Find and remove horizontal lines
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (35,2))
detect_horizontal = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
cnts = cv2.findContours(detect_horizontal, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(thresh, [c], -1, (0,0,0), 3)

# Find and remove vertical lines
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,35))
detect_vertical = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, vertical_kernel, iterations=2)
cnts = cv2.findContours(detect_vertical, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(thresh, [c], -1, (0,0,0), 3)

# Mask out unwanted areas for result
result = cv2.bitwise_and(image,image,mask=thresh)
result[thresh==0] = (255,255,255)

cv2.imshow('thresh', thresh)
cv2.imshow('result', result)
cv2.waitKey()