How to detect the horizontal and vertical lines of a table and eliminate the noise?

风流意气都作罢 提交于 2020-08-05 06:00:09

问题


I am trying to get the horizontal and vertical lines of the table in an image in order to extract the texts in cells. Here's a picture I use:

I use the code below to extract the vertical and horizontal lines:

img = cv2.imread(img_for_box_extraction_path, 0)  # Read the image
(thresh, img_bin) = cv2.threshold(img, 200, 255,
                                  cv2.THRESH_BINARY | cv2.THRESH_OTSU)  # Thresholding the image
img_bin = 255-img_bin  # Invert the image
cv2.imwrite("Image_bin_2.jpg",img_bin)

# Defining a kernel length
kernel_length = np.array(img).shape[1]//140

# A verticle kernel of (1 X kernel_length), which will detect all the verticle lines from the image.
verticle_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, kernel_length))

# A horizontal kernel of (kernel_length X 1), which will help to detect all the horizontal line from the image.
hori_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (kernel_length, 1))

# A kernel of (3 X 3) ones.
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))

# Morphological operation to detect verticle lines from an image
img_temp1 = cv2.erode(img_bin, verticle_kernel, iterations=3)
verticle_lines_img = cv2.dilate(img_temp1, verticle_kernel, iterations=3)
cv2.imwrite("verticle_lines_2.jpg",verticle_lines_img)

# Morphological operation to detect horizontal lines from an image
img_temp2 = cv2.erode(img_bin, hori_kernel, iterations=3)
horizontal_lines_img = cv2.dilate(img_temp2, hori_kernel, iterations=3)
cv2.imwrite("horizontal_lines_2.jpg",horizontal_lines_img)

The pictures below are the horizontal lines and vertical lines:

I use the code below to add two image together

# Weighting parameters, this will decide the quantity of an image to be added to make a new image.
alpha = 0.5
beta = 1.0 - alpha

# This function helps to add two image with specific weight parameter to get a third image as summation of two image.
img_final_bin = cv2.addWeighted(verticle_lines_img, alpha, horizontal_lines_img, beta, 0.0)
img_final_bin = cv2.erode(~img_final_bin, kernel, iterations=2)
(thresh, img_final_bin) = cv2.threshold(img_final_bin, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)

# For Debugging
# Enable this line to see verticle and horizontal lines in the image which is used to find boxes
cv2.imwrite("img_final_bin_2.jpg",img_final_bin)

However, I get a picture like this: How do I remove the noise and get a better result? Thanks in advance.


回答1:


Here's a simple method:

Binary image

Detected horizontal

Detected vertical

Combined masks

Lines to be removed in green

Result

import cv2
import numpy as np

# Load image, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3,3), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Detect horizontal lines
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (50,1))
horizontal_mask = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=1)

# Detect vertical lines
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,50))
vertical_mask = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, vertical_kernel, iterations=1)

# Combine masks and remove lines
table_mask = cv2.bitwise_or(horizontal_mask, vertical_mask)
image[np.where(table_mask==255)] = [255,255,255]

cv2.imshow('thresh', thresh)
cv2.imshow('horizontal_mask', horizontal_mask)
cv2.imshow('vertical_mask', vertical_mask)
cv2.imshow('table_mask', table_mask)
cv2.imshow('image', image)
cv2.waitKey()



回答2:


Try reduce with CV_REDUCE_AVG flag along horizontal for your first binary image and then anlong vertical direction for your second one. Threshols histograms you'll get. And use them to filter your lines.

As an alternative, you can try hough lines detector and filter lines by length and algle.



来源:https://stackoverflow.com/questions/60521925/how-to-detect-the-horizontal-and-vertical-lines-of-a-table-and-eliminate-the-noi

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