在OpenCV中裁剪图像

Question

在OpenCV中裁剪图像

opencvimage-processingtexthough-transform

3

我有一张图片，其中有一些文字。我想要将这张图片发送到OCR进行识别，但是图片中存在一些噪音，因此OCR的结果并不理想。我曾试图通过腐蚀/膨胀图像来获取完美的阈值，但未能成功。由于所有图像中的文本都将完全水平，所以我尝试使用霍夫变换。

当我运行OpenCV捆绑的示例霍夫变换程序时，图像的样子如下： 问题：

如何将除红线所在区域之外的所有内容涂黑？或者如何裁剪出每个被红线圈起来的区域的不同图片？
我只想专注于水平线条，可以舍弃倾斜线条。

对于我来说，任何一种选项都可以用于发送到OCR。但是，我想尝试两种方法，看看哪一种的效果更好。

- birdy

1个回答

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- Zaw Lin · Accepted Answer

如何只保留红线所在区域的内容？

使用dotess2()
输出：['Footel text goes he: e\n', 'Some mole hele\n', 'Some Text Here\n']

或者，如何裁剪出每个红线所示区域的单独图像？

使用dotess1()
输出：['Foolel text goes he: e\n', 'Some mole hele\n', 'Some Text Here\n', 'Directions\n']

代码：

# -*- coding: utf-8 -*- 
import cv2
import numpy as np
import math
import subprocess
import os
import operator

#some clean up/init blah blah
junk='\/,-‘’“ ”?.\';!{§_~!@#$%^&*()_+-|:}»£[]¢€¥°><'
tmpdir='./tmp'
if not os.path.exists(tmpdir):
    os.makedirs(tmpdir)
for path, subdirs, files in os.walk(tmpdir):
    for name in files:
        os.remove(os.path.join(path, name))     

#when the preprocessor is not pefect, there will be junk in the result. this is a crude mean of ridding them off
def resfilter(res):
    rd = dict()
    for l in set(res):
        rd[l]=0.

    for l in rd:
        for i in l:
            if i in junk:
                rd[l]-=1
            elif i.isdigit():
                rd[l]+=.5
            else:
                rd[l]+=1
    ret=[]
    for v in sorted(rd.iteritems(), key=operator.itemgetter(1), reverse=True):
        ret.append(v[0])
    return ret

def dotess1():
    res =[]
    for path, subdirs, files in os.walk(tmpdir):
        for name in files:
            fpath = os.path.join(path, name)
            img = cv2.imread(fpath)
            gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

            '''
            #if the text is too small/contains noise etc, resize and maintain aspect ratio
            if gray.shape[1]<100:
                gray=cv2.resize(gray,(int(100/gray.shape[0]*gray.shape[1]),100))
            '''     
            cv2.imwrite('tmp.jpg',gray)
            args = ['tesseract.exe','tmp.jpg','tessres','-psm','7', '-l','eng']
            subprocess.call(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE) 
            with open('tessres.txt') as f:
                    for line in f:
                        if line.strip() != '':
                            res.append(line)
    print resfilter(res)


def dotess2():
    res =[]
    args = ['tesseract.exe','clean.jpg','tessres','-psm','3', '-l','eng']
    subprocess.call(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE) 
    with open('tessres.txt') as f:
            for line in f:
                if line.strip() != '':
                    res.append(line)
    print resfilter(res)

'''
start of code
'''
img = cv2.imread('c:/data/ocr3.png')
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
canny=cv2.Canny(gray,50,200,3)
cv2.imshow('canny',canny)

#remove the actual horizontal lines so that hough wont detect them
linek = np.zeros((11,11),dtype=np.uint8)
linek[5,...]=1
x=cv2.morphologyEx(canny, cv2.MORPH_OPEN, linek ,iterations=1)
canny-=x
cv2.imshow('canny no horizontal lines',canny)

#draw a fat line so that you can box it up
lines = cv2.HoughLinesP(canny, 1, math.pi/2, 50,50, 50, 20)
linemask = np.zeros(gray.shape,gray.dtype)
for line in lines[0]:
    if line[1]==line[3]:#check horizontal
        pt1 = (line[0],line[1])
        pt2 = (line[2],line[3])
        cv2.line(linemask, pt1, pt2, (255), 30)

cv2.imshow('linemask',linemask)

'''
* two methods of doing ocr,line mode and page mode
* boxmask is used to so that a clean image can be saved for page mode
* for every detected boxes, the roi are cropped and saved so that tess3 can be run in line mode
'''

boxmask = np.zeros(gray.shape,gray.dtype)
contours,hierarchy = cv2.findContours(linemask,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
idx=0
for cnt in contours:
    idx+=1
    area = cv2.contourArea(cnt)
    x,y,w,h = cv2.boundingRect(cnt)
    roi=img[y:y+h,x:x+w].copy()
    cv2.imwrite('%s/%s.jpg'%(tmpdir,str(idx)),roi)
    cv2.rectangle(boxmask,(x,y),(x+w,y+h),(255),-1)


cv2.imshow('clean',img&cv2.cvtColor(boxmask,cv2.COLOR_GRAY2BGR))
cv2.imwrite('clean.jpg',img&cv2.cvtColor(boxmask,cv2.COLOR_GRAY2BGR))
cv2.imshow('img',img)

dotess1()
dotess2()
cv2.waitKey(0)