从图像中重叠的字母中提取数据 [英] extract data from the overlapping letters in a image

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本文介绍了从图像中重叠的字母中提取数据的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

输入图片:

我想从图像(ocr)中提取数据 我尝试过的代码:

i want to extract the data from the image ( ocr ) code which i tried:

    import cv2
    import textract
    import numpy as np
    img = cv2.imread('/home/ajay/Desktop/name.jpg',0)
    # img = cv2.imread('path_to_your_image', 0)
    _, blackAndWhite = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY_INV)
    nlabels, labels, stats, centroids = cv2.connectedComponentsWithStats(blackAndWhite, None, None, None, 8, cv2.CV_32S)
    sizes = stats[1:, -1] #get CC_STAT_AREA component
    img2 = np.zeros((labels.shape), np.uint8)
    for i in range(0, nlabels - 1):
        if sizes[i] >= 50:   #filter small dotted regions
            img2[labels == i + 1] = 255
    res = cv2.bitwise_not(img2)
    cv2.imwrite('ress.png', res)
    a =  textract.process('ress.png',method = 'tesseract')
    a = a.decode()
    print(a)

推荐答案

一个简单的方法是:

  1. 应用锐化内核
  2. 大津的门槛
  3. 应用轻微的高斯模糊
  4. 反转图像
  5. OCR


这是步骤的可视化:


Here's a visualization of the steps:

输入图片

锐化

大津的门槛

轻微的高斯模糊

反转图像

这是使用Pytesseract的OCR结果

Here's the OCR results using Pytesseract

DST INTERNATIONAL D-307@ 3266 01 Dec 2007. HowellJerde Jan!
2007" 125802AM RafaelaBoyer Keon3@gmnil.com Fhvio Abernathy Sr.

代码

import cv2
import numpy as np
import pytesseract

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

image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
sharpen = cv2.filter2D(gray, -1, kernel)

thresh = cv2.threshold(sharpen, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

blur = cv2.GaussianBlur(thresh, (3,3), 0)
invert = 255 - blur
data = pytesseract.image_to_string(invert, lang='eng',config='--psm 6')
print(data)

cv2.imshow('sharpen', sharpen)
cv2.imshow('thresh', thresh)
cv2.imshow('blur', blur)
cv2.imshow('invert', invert)
cv2.waitKey()

这篇关于从图像中重叠的字母中提取数据的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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