用 Python 进行简单的验证码识别

由于模拟登陆的需要，需要做验证码识别

基本原理

简单验证码识别主要原理还是建立模型 > 去噪点 > 二值化 > 对比如果是复杂一点的验证码则另论下面简单介绍简单验证码的识别

大致思路

先打开原始图片

import Image
im = Image.open("temp.jpg")

图片灰度处理

im = im.convert('L')

灰度处理后的效果

根据阀值(threshold)生成表 table 再根据 table 对图片二值化处理

threshold = 140
table = [0 if i < threshold else 1 for i in range(256)]
im = im.point(table, '1')

二值化处理后的效果

将二值化后的图片转为字符串

im_data = ''.join(str(x) for x in list(im.getdata()))

这时候就会得到图片对应的字符串，将字符串与数据库进行比较，就可以了（当然这里的验证码分割后会更好处理）

完整的验证码识别代码

定义图片的一些基本信息(图片的一些基本信息，识别过程中也可以随时调整)

#验证码图片数量
imgNum = 100
#灰度阀值
threshold = 127
table = [0 if i < threshold else 1 for i in range(256)]
#图片信息
info = {
    "offsetWidth": 2,   #宽度偏移
    "offsetHeight": 4,  #高度偏移
    "wordNum": 4,       #字符数量
    "wordWidth": 12,    #字符宽度
    "wordHeight": 12,   #字符高度
    "wordSpace": -2     #字符空隙
}

获取验证码图片

import requests
cookies = requests.get('http://www.domain.com').cookies
for i in range(imgNum):
    img = requests.get('http://www.domain.com', cookies = cookies).content
    with open('code/%s.jpg' % i, 'w') as f:
        f.write(img)

验证码图片分割,分割为单个字符一个图片

import Image
for i in range(imgNum):
    im = Image.open("code/%s.jpg" % i)
    #分割单个字符
    for j in range(info['wordNum']):
        beginX = info['offsetWidth'] + (info['wordWidth'] + info['wordSpace']) * j
        beginY = info['offsetHeight']
        endX = beginX + info['wordWidth']
        endY = beginY + info['wordHeight']
        box = (beginX, beginY, endX, endY)
        im.crop(box).save('part/%s-%s.jpg' % (i,j))

分割后部分图片效果

图片手动选择

这一步我处理的很蛋痛
这一步的目的就是用后面的代码生成数据库
操作方法：手动选择较好的图片并将图片

手动分类

灰度处理后二值化，然后统计，生成字符数据库

import os
keys = {}
path = "part/"
folders = [x for x in os.listdir(path) if os.path.isdir(path + x)]
for key in folders:
    imgFlag = []
    tmpPath = path + key + '/'
    files = [tmpPath + x for x in os.listdir(tmpPath) if os.path.isfile(tmpPath + x)]
    for img in files:
    im = Image.open(img).convert('L')
    im = im.point(table, '1')
    imgData = ''.join(str(x) for x in list(im.getdata()))
    for i in range(len(imgData)):
        if(len(imgFlag) <= i):
            imgFlag.append([0,0])
        imgFlag[i][int(imgData[i])] += 1
keys[key] = ''.join('0' if flag[0] > flag[1] else '1' for flag in imgFlag)

正常情况下，每个字符对应的值就存放在 keys 里面了，可以输出看看

import json
print json.dumps(keys, indent=2)

输出的结果如下：

{
  "c": "111111111111111111111111111111111111111100001111111000000111110001101111110011111111110011111111110011111111110001111111111000001111111100011111",
  "b": "111111111111110011111111110011111111110000001111110000000111110001100011110011110011110011110011110011110011110001100011110000000111111000001111",
  "m": "111111111111111111111111111111111111111000001100110000000000110001000010110011100111110011100111110011100111110011100111110011100111111111111111",
  "n": "111111111111111111111111111111111111111000000111110000000011110001100011110011110011110011110011110011110011110011110011110011110011111111111111",
  "1": "111110111111111100011111111000011111111000011111111110011111111110011111111110011111111110011111111110011111111110011111111110011111111111111111",
  "3": "111000001111110000000111111111000111111111000111111110001111111110001111111111000111111111100111110111100111100011000111110000001111111000011111",
  "2": "111000011111110000001111100011000111110111100111111111100111111111001111111110001111111100011111111000111111110000111111100000001111110000001111",
  "v": "111111111111111111111111111111111111111111111111110011100111110011100111111001001111111000001111111000001111111100011111111100011111111110111111",
  "x": "111111111111111111111111111111111111111011101111110001000111111000001111111100011111111100011111111100011111111000001111110001000111111011101111",
  "z": "111111111111111111111111111111111111111000001111111000000111111110001111111110001111111100011111111000111111111000111111110000001111111000001111"
}

现在数据库也有了，那么可以进入识别阶段了

验证码识别

import difflib
for i in range(imgNum):
    codes = code = ""
    im = Image.open("code/%s.bmp" % i).convert('L')
    #分割单个字符
    for j in range(info['wordNum']):
        beginX = info['offsetWidth'] + (info['wordWidth'] + info['wordSpace']) * j
        beginY = info['offsetHeight']
        endX = beginX + info['wordWidth']
        endY = beginY + info['wordHeight']
        box = (beginX, beginY, endX, endY)
        imgData = ''.join(['0' if x > threshold else '1' for x in list(im.crop(box).
        getdata())])
        percent = maxPercent=0.0
        #选取相似度最大的值
        for key in keys:
            percent = difflib.SequenceMatcher(None, imgData,keys[key]).ratio()
            if percent > maxPercent:
                maxPercent = percent
                code = key
            codes += code
    print i, codes