python 验证码连通域分割

1.思路是用深度遍历,对图片进行二值化处理,先找到一个黑色像素,然后对这个像素的周围8个像素进行判断,如果没有访问过,就保存起来,然后最后这个数组的最小x和最大x就是x轴上的切割位置。这种分割的方法还是只能适用于没有粘连的验证码,比垂直分割的好处是,可以处理位置比较奇怪的验证码。

def cfs(img):
    """传入二值化后的图片进行连通域分割"""
    pixdata = img.load()
    w,h = img.size
    visited = set()
    q = queue.Queue()
    offset = [(-1,-1),(0,-1),(1,-1),(-1,0),(1,0),(-1,1),(0,1),(1,1)]
    cuts = []
    for x in range(w):
        for y in range(h):
            x_axis = []
            #y_axis = []
            if pixdata[x,y] == 0 and (x,y) not in visited:
                q.put((x,y))
                visited.add((x,y))
            while not q.empty():
                x_p,y_p = q.get()
                for x_offset,y_offset in offset:
                    x_c,y_c = x_p+x_offset,y_p+y_offset
                    if (x_c,y_c) in visited:
                        continue
                    visited.add((x_c,y_c))
                    try:
                        if pixdata[x_c,y_c] == 0:
                            q.put((x_c,y_c))
                            x_axis.append(x_c)
                            #y_axis.append(y_c)
                    except:
                        pass
            if x_axis:
                min_x,max_x = min(x_axis),max(x_axis)
                if max_x - min_x >  3:
                    # 宽度小于3的认为是噪点,根据需要修改
                    cuts.append((min_x,max_x + 1))
    return cuts

def saveSmall(img, outDir, cuts):
    w, h = img.size
    pixdata = img.load()
    for i, item in enumerate(cuts):
        box = (item[0], 0, item[1], h)
        img.crop(box).save(outDir + str(i) + ".png")
img = Image.open('out/51.png')

saveSmall(img, 'cfs/', cfs(img))

参考这篇文章 http://www.hi-roy.com/2017/09/20/Python%E9%AA%8C%E8%AF%81%E7%A0%81%E8%AF%86%E5%88%AB2/

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