豆瓣网登录之验证码识别

最近想着爬下豆瓣网，又不想通过登陆后保存 cookies 的方式登录，故想通过识别网上的验证码，用本身的账号密码登录。

在网上找了一些资料，通过观察豆瓣验证码图片后得到以下思路：
1、豆瓣网的验证码字幕的颜色比较单一，且与背景颜色差异较大，所以可以通过设定一个 GRB 的阈值来二值化图片灰度；
2、对二值化后的图片进行加窗滤波消除噪点；
3、对消除噪点后的图片进行分割；
分割思路：由于豆瓣验证码中的字母无连接，所以可以根据图片在纵轴像素点上累计的非白色点个数来划分字符。
4、对分割后的图片进行识别，可以是自建模板匹配，也可以利用有关的库进行匹配。

注：
1、在本文中由于库安装不全，就没有对分割后的图片做识别了。
2、关于识别率，对于字母笔画粗细均匀的字母，去噪的效果明显好于笔画粗细不均的字母，自然识别率也高一些。
3、基本效果如下：

原始验证码

二值化验证码

去噪处理

分割处理

不多说了，直接上代码。

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from PIL import Image
#import pytesseract

WHITE = (255,255,255)
BLACK = (0,0,0)
#对图片做预处理，去除背景
def pre_concert(img):
    width,height = img.size
    threshold = 30
    for i in range(0,width):
        for j in range(0,height):
            p = img.getpixel((i,j))#抽取每个像素点的像素
            r,g,b = p
            if r > threshold or g > threshold or b > threshold:
                img.putpixel((i,j),WHITE)
            else:
                img.putpixel((i,j),BLACK)
    img.show()
    img.save("pre_fig.jpg")
    return


#对去除背景的图片做噪点处理
def remove_noise(self, window=1):
    if window == 1:
        window_x = [1,0,0,-1,0]
        window_y = [0,1,0,0,-1]
    elif window == 2:
        window_x = [-1,0,1,-1,0,1,1,-1,0]
        window_y = [-1,-1,-1,1,1,1,0,0,0]

    width,height = self.size
    for i in range(width):
        for j in range(height):
            box = []

            for k in range(len(window_x)):
                d_x = i + window_x[k]
                d_y = j + window_y[k]
                try:
                    d_point = self.getpixel((d_x,d_y))
                    if d_point == BLACK:
                        box.append(1)
                    else:
                        box.append(0)
                except IndexError:
                        self.putpixel((i,j),WHITE)
                        continue

            box.sort()
            if len(box) == len(window_x):
                mid = box[int(len(box)/2)]
                if mid == 1:
                    self.putpixel((i,j),BLACK)
                else:
                    self.putpixel((i,j),WHITE)
    self.show()
    self.save("mov_noise_fig.jpg")
    return


def split_fig(self):
    frame = self.load()
    img_new = self.copy()
    frame_new = img_new.load()

    width,height = self.size
    line_status = None
    pos_x = []
    for x in range(width):
        pixs = []
        for y in range(height):
            pixs.append(frame[x,y])

        if len(set(pixs)) == 1:
            _line_status = 0
        else:
            _line_status = 1

        if _line_status != line_status:
            if _line_status != None:
                if _line_status == 0:
                    _x = x
                elif _line_status == 1:
                    _x = x - 1

                pos_x.append(_x)

                #辅助线
                for _y in range(height):
                    frame_new[x,_y] = BLACK

        line_status = _line_status

    img_new.show()
    img_new.save("split_fig.jpg")


    i = 0
    divs = []
    boxs = []
    while True:
        try:
            x_i = pos_x[i]
            x_j = pos_x[i+1]
        except:
            break

        i = i + 2
        boxs.append([x_i,x_j])

    fixed_boxs = []
    i = 0
    while i < len(boxs):
        box = boxs[i]
        if box[1] - box[0] < 10:
            try:
                box_next = boxs[i+1]
                fixed_boxs.append([box[0],box_next[1]])
                i += 2
            except Exception:
                break
        else:
            fixed_boxs.append(box)
            i += 1

    for box in fixed_boxs:
        div = self.crop((box[0],0,box[1],height))
        try:
            #divs.append(format_div(div,size=(20,40)))
            divs.append(div)
        except:
            divs.append(div)

    #过滤掉非字符的切片
    _divs = []
    for div in divs:
        width,heigth = div.size
        if width < 5:
            continue

        frame = div.load()
        points = 0
        for i in range(width):
            for j in range(heigth):
                p = frame[i,j]
                if p == BLACK:
                    points += 1

        if points <= 5:
            continue

        #new_div = format_div(div)
        new_div = div
        _divs.append(new_div)
    return _divs



def image_to_string(img,config='-psm 8'):
    try:
        result = pytesseract.image_to_string(img,lang='eng',config=config)
        result = result.strip()
        return result.lower()
    except:
        return None


#测试代码
def main():
    img = Image.open("fig2.jpg")
    pre_concert(img)
    remove_noise(img,2)
    img1 = split_fig(img)
    #image_to_string(img1,config='-psm 8')


if __name__ == '__main__':
    main()