验证码识别 图像降噪 Python (一）

原始图片：

降噪后的图片

 

实现代码：

# coding:utf-8
import sys, os
from PIL import Image, ImageDraw

# 二值数组
t2val = {}


def twoValue(image, G):
    for y in xrange(0, image.size[1]):
        for x in xrange(0, image.size[0]):
            g = image.getpixel((x, y))
            if g > G:
                t2val[(x, y)] = 1
            else:
                t2val[(x, y)] = 0


# 根据一个点A的RGB值，与周围的8个点的RBG值比较，设定一个值N（0 <N <8），当A的RGB值与周围8个点的RGB相等数小于N时，此点为噪点
# G: Integer 图像二值化阀值
# N: Integer 降噪率 0 <N <8
# Z: Integer 降噪次数
# 输出
#  0：降噪成功
#  1：降噪失败
def clearNoise(image, N, Z):
    for i in xrange(0, Z):
        t2val[(0, 0)] = 1
        t2val[(image.size[0] - 1, image.size[1] - 1)] = 1

        for x in xrange(1, image.size[0] - 1):
            for y in xrange(1, image.size[1] - 1):
                nearDots = 0
                L = t2val[(x, y)]
                if L == t2val[(x - 1, y - 1)]:
                    nearDots += 1
                if L == t2val[(x - 1, y)]:
                    nearDots += 1
                if L == t2val[(x - 1, y + 1)]:
                    nearDots += 1
                if L == t2val[(x, y - 1)]:
                    nearDots += 1
                if L == t2val[(x, y + 1)]:
                    nearDots += 1
                if L == t2val[(x + 1, y - 1)]:
                    nearDots += 1
                if L == t2val[(x + 1, y)]:
                    nearDots += 1
                if L == t2val[(x + 1, y + 1)]:
                    nearDots += 1

                if nearDots < N:
                    t2val[(x, y)] = 1


def saveImage(filename, size):
    image = Image.new("1", size)
    draw = ImageDraw.Draw(image)

    for x in xrange(0, size[0]):
        for y in xrange(0, size[1]):
            draw.point((x, y), t2val[(x, y)])

    image.save(filename)
for i in range(1,21):
    path = "/" + str(i) + ".jpg"
    image = Image.open(path).convert("L")
    twoValue(image, 100)
    clearNoise(image, 2, 1)
    path1 = "/" + str(i) + ".png"
    saveImage(path1, image.size)