如何从验证码中完全删除行

how to remove line from captcha completely

我编写了一个程序来从这个验证码中删除该行:

首先,我通过中值滤波器提高图像可见性

def apply_median_filter(self,img):
    img_gray=img.convert('L')
    img_gray=cv2.medianBlur(np.asarray(img_gray),3)
    img_bw=(img_gray>np.mean(img_gray))*255
    return img_bw

然后我尝试删除行:

def eliminate_zeros(self,vector):
    return [(dex,v) for (dex,v) in enumerate(vector) if v!=0 ]

def get_line_position(self,img):
    sumx=img.sum(axis=0)
    list_without_zeros=self.eliminate_zeros(sumx)
    min1,min2=heapq.nsmallest(2,list_without_zeros,key=itemgetter(1))
    l=[dex for [dex,val] in enumerate(sumx) if val==min1[1] or val==min2[1]]
    mindex=[l[0],l[len(l)-1]]
    cols=img[:,mindex[:]]
    col1=cols[:,0]
    col2=cols[:,1]
    col1_without_0=self.eliminate_zeros(col1)
    col2_without_0=self.eliminate_zeros(col2)
    line_length=len(col1_without_0)
    dex1=col1_without_0[round(len(col1_without_0)/2)][0]
    dex2=col2_without_0[round(len(col2_without_0)/2)][0]
    p1=[dex1,mindex[0]]
    p2=[dex2,mindex[1]]
    return p1,p2,line_length

最后我删除了行的位置:

def remove_line(self,p1,p2,LL,img):
    m=(p2[0]-p1[0])/(p2[1]-p1[1]) if p2[1]!=p1[1] else np.inf
    w,h=len(img),len(img[0])
    x=[x for x in range(w)]
    y=[p1[0]+k for k in [m*t for t in [v-p1[1] for v in x]]]
    img_removed_line=img
    for dex in range(w):
        i,j=np.round([y[dex],x[dex]])
        i=int(i)
        j=int(j)
        rlist=[]
        while True:
            f1=i
            if img_removed_line[i,j]==0 and img_removed_line[i-1,j]==0:
                break
            rlist.append(i)
            i=i-1

        i,j=np.round([y[dex],x[dex]])
        i=int(i)
        j=int(j)
        while True:
            f2=i
            if img_removed_line[i,j]==0 and img_removed_line[i+1,j]==0:
                break
            rlist.append(i)
            i=i+1
        print([np.abs(f2-f1),[LL+1,LL,LL-1]])
        if np.abs(f2-f1) in [LL+1,LL,LL-1]:
            rlist=list(set(rlist))
            img_removed_line[rlist,j]=0

    return img_removed_line

但在某些情况下线条没有完全删除,我得到的验证码图像有一些噪音:

非常感谢您的帮助!

问题已解决!这是我编辑的 python 代码。这从验证码中删除了行。希望对您有所帮助:

from PIL import Image,ImageFilter
from scipy.misc import toimage
from operator import itemgetter
from skimage import measure
import numpy as np
import copy
import heapq
import cv2
import matplotlib.pyplot as plt
from scipy.ndimage.filters import median_filter

#----------------------------------------------------------------
class preprocessing:  
def pre_proc_image(self,img):
    #img_removed_noise=self.apply_median_filter(img)
    img_removed_noise=self.remove_noise(img)
    p1,p2,LL=self.get_line_position(img_removed_noise)
    img=self.remove_line(p1,p2,LL,img_removed_noise)
    img=median_filter(np.asarray(img),1)
    return img

def remove_noise(self,img):
    img_gray=img.convert('L')
    w,h=img_gray.size
    max_color=np.asarray(img_gray).max()
    pix_access_img=img_gray.load()
    row_img=list(map(lambda x:255 if x in range(max_color-15,max_color+1) else 0,np.asarray(img_gray.getdata())))
    img=np.reshape(row_img,[h,w])
    return img

def apply_median_filter(self,img):
    img_gray=img.convert('L')
    img_gray=cv2.medianBlur(np.asarray(img_gray),3)
    img_bw=(img_gray>np.mean(img_gray))*255
    return img_bw

def eliminate_zeros(self,vector):
    return [(dex,v) for (dex,v) in enumerate(vector) if v!=0 ]

def get_line_position(self,img):
    sumx=img.sum(axis=0)
    list_without_zeros=self.eliminate_zeros(sumx)
    min1,min2=heapq.nsmallest(2,list_without_zeros,key=itemgetter(1))
    l=[dex for [dex,val] in enumerate(sumx) if val==min1[1] or val==min2[1]]
    mindex=[l[0],l[len(l)-1]]
    cols=img[:,mindex[:]]
    col1=cols[:,0]
    col2=cols[:,1]
    col1_without_0=self.eliminate_zeros(col1)
    col2_without_0=self.eliminate_zeros(col2)
    line_length=len(col1_without_0)
    dex1=col1_without_0[round(len(col1_without_0)/2)][0]
    dex2=col2_without_0[round(len(col2_without_0)/2)][0]
    p1=[dex1,mindex[0]]
    p2=[dex2,mindex[1]]
    return p1,p2,line_length

def remove_line(self,p1,p2,LL,img):
    m=(p2[0]-p1[0])/(p2[1]-p1[1]) if p2[1]!=p1[1] else np.inf
    w,h=len(img),len(img[0])
    x=list(range(h))
    y=list(map(lambda z : int(np.round(p1[0]+m*(z-p1[1]))),x))
    img_removed_line=list(img)
    for dex in range(h):
        i,j=y[dex],x[dex]  
        i=int(i)
        j=int(j)
        rlist=[]
        while True:
            f1=i
            if img_removed_line[i][j]==0 and img_removed_line[i-1][j]==0:
                break
            rlist.append(i)
            i=i-1

        i,j=y[dex],x[dex]
        i=int(i)
        j=int(j)
        while True:
            f2=i
            if img_removed_line[i][j]==0 and img_removed_line[i+1][j]==0:
                break
            rlist.append(i)
            i=i+1
        if np.abs(f2-f1) in [LL+1,LL,LL-1]:
            rlist=list(set(rlist))
            for k in rlist:
                img_removed_line[k][j]=0

    return img_removed_line