tesseract 验证码识别前预处理之去干扰线

Posted 2021-05-01 我的时光穿梭机

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常见干扰线有以下几种模式。针对不同模式，采用不同策略处理可达到较好的效果。此处未穷举所有可能的模式，但可以发现，处理方法分两种：一是利用目标字符和背景的色彩差异，二是利用目标字符和背景的形状差异。在背景颜色固定且与目标字符颜色差异较大时，用色差法处理效果较佳；在背景颜色与目标字符颜色差异较小甚至无差异时，可针对二者呈现出的不同形态规律编写相应算法进行处理。

from PIL import Image
import numpy as np
import cv2
imgpath = r'C:\Users\Kelv\Pictures\Veri_codes\test66.png'
img2 = Image.open(imgpath)
# 最后一个参数是alpha通道设置值，决定所处理区域的透明度，0表示背景完全透明，255表示背景不透明。这一参数必须在'RGBA'模式下使用。有关图片模式，可参考 https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
img2 = img2.convert('RGBA')
for y in range(img2.size[1]):
    for x in range(img2.size[0]):
        try:
            r,g,b,a = img2.getpixel((x,y))
            # Method 1:
            # for regularly repeated background patterns
            # if (r,g,b) == (128,191,255) or (r,g,b) == (227,218,237):
                # r,g,b,a = (255,255,255,255)
            # Method 2:
            # for randomly distributed fixed-shape dots
            # if 55<r<75 and 1<g<20 and 10<b<20:
                # r,g,b,a = (255,255,255,255)
                # for i in range(-8,8):
                    # for j in range(-8,8):
                        # img2.putpixel((x+i,y+j),(r,g,b,a))
            # Method 3:
            # for straight line in specific colors
            # if (148<r<255 and 108<g<248 and 0<=b<130) or (210<r<255 and 183<g<244 and 134<=b<194) \
            # or (219<r<255 and 183<g<244 and 200<=b<255) or (23<r<80 and 33<g<55 and 0<=b<45) \
            # or (67<r<127 and 43<g<100 and 31<=b<110) or (167<r<187 and 123<g<143 and 81<=b<101) \
            # or (87<r<147 and 130<g<144 and 101<=b<170):
                # r,g,b,a = (255,255,255,255)
                # img2.putpixel((x,y),(r,g,b,a))
            # Method 4-1:
            # for cubic-pixel line
            if (r,g,b) ==(101,101,254) or (r,g,b) ==(254,101,101):
                if \
                    (img2.getpixel((x,y)) == img2.getpixel((x+1,y)) \
                    and img2.getpixel((x,y)) == img2.getpixel((x,y+1)) \
                    and img2.getpixel((x,y)) == img2.getpixel((x+1,y+1))):
                    r,g,b,a = (255,255,255,255)
                    img2.putpixel((x,y),(r,g,b,a))
                    img2.putpixel((x+1,y),(r,g,b,a))
                    img2.putpixel((x,y+1),(r,g,b,a))
                    img2.putpixel((x+1,y+1),(r,g,b,a))
            Method 4-2:
                if \
                    np.sum((r,g,b)) == np.sum(img2.getpixel((x+1,y))[:3]+img2.getpixel((x,y+1))[:3])/2:
                    r,g,b,a = (255,255,255,255)
                    img2.putpixel((x,y),(r,g,b,a))
                    img2.putpixel((x+1,y),(r,g,b,a))
                    img2.putpixel((x,y+1),(r,g,b,a))
                elif \
                    np.sum((r,g,b)) == np.sum(img2.getpixel((x-1,y))[:3]+img2.getpixel((x,y+1))[:3])/2:
                    r,g,b,a = (255,255,255,255)
                    img2.putpixel((x,y),(r,g,b,a))
                    img2.putpixel((x-1,y),(r,g,b,a))
                    img2.putpixel((x,y+1),(r,g,b,a))
                elif \
                    np.sum((r,g,b)) == np.sum(img2.getpixel((x-1,y))[:3]+img2.getpixel((x,y-1))[:3])/2:
                    r,g,b,a = (255,255,255,255)
                    img2.putpixel((x,y),(r,g,b,a))
                    img2.putpixel((x-1,y),(r,g,b,a))
                    img2.putpixel((x,y-1),(r,g,b,a))
                elif \
                    np.sum((r,g,b)) == np.sum(img2.getpixel((x+1,y))[:3]+img2.getpixel((x,y-1))[:3])/2:
                    r,g,b,a = (255,255,255,255)
                    img2.putpixel((x,y),(r,g,b,a))
                    img2.putpixel((x+1,y),(r,g,b,a))
                    img2.putpixel((x,y-1),(r,g,b,a))
                Method 4-3:
                totalpixel = \
                np.sum((\
                img2.getpixel((x-1,y-1)),img2.getpixel((x,y-1)),img2.getpixel((x+1,y-1)), \
                img2.getpixel((x-1,y)) ,img2.getpixel((x+1,y)), \
                img2.getpixel((x-1,y+1)),img2.getpixel((x,y+1)),img2.getpixel((x+1,y+1))))
                if  totalpixel == np.sum((255,255,255,255))*8 or \
                    totalpixel == np.sum((255,255,255,255))*7+np.sum((r,g,b,a)):
                if \
                img2.getpixel((x-1,y-1))==img2.getpixel((x,y-1))==img2.getpixel((x+1,y-1)) \
                ==img2.getpixel((x-1,y)) ==img2.getpixel((x+1,y)) \
                ==img2.getpixel((x-1,y+1))==img2.getpixel((x,y+1))==img2.getpixel((x+1,y+1)) == (255,255,255,255):
                    r,g,b,a = (255,255,255,255)
                    img2.putpixel((x,y),(r,g,b,a))
                    img2.putpixel((x,y-1),(r,g,b,a))
                    img2.putpixel((x,y+1),(r,g,b,a))
                    img2.putpixel((x-1,y),(r,g,b,a))
                    img2.putpixel((x+1,y),(r,g,b,a))
                    img2.putpixel((x-1,y-1),(r,g,b,a))
                    img2.putpixel((x+1,y-1),(r,g,b,a))
                    img2.putpixel((x+1,y+1),(r,g,b,a))
                    img2.putpixel((x-1,y+1),(r,g,b,a))
        except Exception as e:
            print(e)
            continue
img2.save(imgpath.split('.')[0]+'x.png')
img2.show()