ocr_cv2

Use only opencv morphology libraries.

import cv2

import numpy as np

import os

import matplotlib.pyplot as plt

folder = r'C:\data\test data'

files = [os.path.join(folder, f) for f in os.listdir(folder)]

# Read pictures

imagePath = files[0]

img = cv2.imread(imagePath)

# Converting to Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray Gray

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Using Sobel Edge Detection to Generate Binary Graph

sobel = cv2.Sobel(gray, cv2.CV_8U, 1, 0, ksize=3)

# Two valued

ret, binary = cv2.threshold(sobel, 0, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)

# Expansion and Corrosion

element1 = cv2.getStructuringElement(cv2.MORPH_RECT, (30, 9))

element2 = cv2.getStructuringElement(cv2.MORPH_RECT, (24, 6))

# Expansion once to make the outline stand out

dilation = cv2.dilate(binary, element2, iterations=1)

# Corrode once, remove details

erosion = cv2.erode(dilation, element1, iterations=1)

# Expansion again to make the outline more visible

dilation2 = cv2.dilate(erosion, element2, iterations=2)

#  Finding Outlines and Screening Text Areas

region = []

contours, hierarchy = cv2.findContours(dilation2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

for i in range(len(contours)):

    cnt = contours[i]

    # Calculate contour area and screen out small areas

    area = cv2.contourArea(cnt)

    if (area < 1000):

        continue

    # Find the smallest rectangle

    rect = cv2.minAreaRect(cnt)

    print ("rect is: ")

    print (rect)

    # box is the coordinate of four points

    box = cv2.boxPoints(rect)

    box = np.int0(box)

    # Computing height and width

    height = abs(box[0][1] - box[2][1])

    width = abs(box[0][0] - box[2][0])

    # According to the characteristics of the text, select those too thin rectangles, leaving flat ones.

    if (height > width * 1.3):

        continue

    region.append(box)

# Draw outline

for box in region:

    cv2.drawContours(img, [box], 0, (0, 255, 0), 2)

plt.figure(figsize=(30,20))

plt.imshow(img)

plt.show()

# cv2.imshow('img', img)

# cv2.waitKey(0)

# cv2.destroyAllWindows()