我写了一个程序来删除此验证码中的行：

首先,我通过中值滤波器改善图像可见性

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

最后我按其位置删除了行：

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,线条并未完全移除,我得到的验证码图像有一些噪音：

非常感谢您的帮助！

解决方法:

问题已经解决了！这是我编辑的python代码.这会从验证码中删除一行.我希望它有所帮助：

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