使用python 对验证码图片进行降噪处理

from PIL import Image
 
# 二值化处理
def two_value():
  for i in range(1,5):
    # 打开文件夹中的图片
    image=Image.open('./Img/'+str(i)+'.jpg')
    # 灰度图
    lim=image.convert('L')
    # 灰度阈值设为165，低于这个值的点全部填白色
    threshold=165
    table=[]
    
    for j in range(256):
      if j<threshold:
        table.append(0)
      else:
        table.append(1)
 
    bim=lim.point(table,'1')
    bim.save('./Img2/'+str(i)+'.jpg')
 
two_value()

from PIL import Image
 
# 去除干扰线
im = Image.open('./Img2/1.jpg')
# 图像二值化
data = im.getdata()
w,h = im.size
black_point = 0
 
for x in range(1,w-1):
  for y in range(1,h-1):
    mid_pixel = data[w*y+x] # 中央像素点像素值
    if mid_pixel <50: # 找出上下左右四个方向像素点像素值
      top_pixel = data[w*(y-1)+x]
      left_pixel = data[w*y+(x-1)]
      down_pixel = data[w*(y+1)+x]
      right_pixel = data[w*y+(x+1)]
 
      # 判断上下左右的黑色像素点总个数
      if top_pixel <10:
        black_point += 1
      if left_pixel <10:
        black_point += 1
      if down_pixel <10:
        black_point += 1
      if right_pixel <10:
        black_point += 1
      if black_point <1:
        im.putpixel((x,y),255)
      # print(black_point)
      black_point = 0
 
im.save('xxxx.jpg')

from PIL import Image
 
# 去除干扰线
im = Image.open('./Img2/1.jpg')
# 图像二值化
data = im.getdata()
w,h = im.size
black_point = 0
 
for x in range(1,w-1):
  for y in range(1,h-1):
    if x<2 or y<2 :
      im.putpixel((x-1, y-1), 255)
    if x>w-3 or y>h-3:
      im.putpixel((x+1 , y+1 ), 255)
 
im.save('xxx.jpg')