去除图像的颜色 [英] Remove color from an image

问题描述

我想从下面的图像中删除颜色，由于这种颜色，我无法从图像中清楚地提取文本.

I want to remove the color from the below image, due to this color I am unable to extract the text clearly from the image.

我正在使用下面的代码，但是我没有得到清晰的文字，

I am using the below code, but I am not getting the clear text,

import numpy as np
from PIL import Image

im = Image.open('my_file.tif')
im = im.convert('RGBA')
data = np.array(im)
# just use the rgb values for comparison
rgb = data[:,:,:3]
color = [246, 213, 139]   # Original value
black = [0,0,0, 255]
white = [255,255,255,255]
mask = np.all(rgb == color, axis = -1)
# change all pixels that match color to white
data[mask] = white

# change all pixels that don't match color to black
##data[np.logical_not(mask)] = black
new_im = Image.fromarray(data)
new_im.save('new_file.tif')

和

def black_and_white(input_image_path,
                output_image_path):
color_image = Image.open(input_image_path)
bw = color_image.convert('L')
bw.save(output_image_path)

请帮助我...

图片2:

推荐答案

我假设您要提取报价.为此，您可以执行一系列过滤操作以删除非文本轮廓.获得处理结果后，可以使用Pytesseract等OCR工具提取文本.

I'm assuming you want to extract the quote. To do this, you can do a series of filtering operations to remove non-text contours. Once you have the processed result you can use an OCR tool such as Pytesseract for text extraction.

OCR的结果

On behalf of the hundreds of ACLU activists who
called on Governor Walker to veto House Bill
156, we are disappointed that he did not put
students or the Constitution first today."
—Joshua A. Decker
Executive Director

代码

import cv2
import pytesseract

pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"

# Load image and threshold
image = cv2.imread('1.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Connect text with a horizontal shaped kernel
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10,3))
dilate = cv2.dilate(thresh, kernel, iterations=3)

# Remove non-text contours using aspect ratio filtering
cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    aspect = w/h
    if aspect < 3:
        cv2.drawContours(thresh, [c], -1, (0,0,0), -1)

# Invert image and OCR
result = 255 - thresh
data = pytesseract.image_to_string(result, lang='eng',config='--psm 6')
print(data)

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

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