import cv2
#/////////////////////1、读取图像,并把图像转换为灰度图像并显示
img = cv2.imread("D:/xunlei/2.png") # 读取图片
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 转换了灰度化
cv2.imshow('gray', img_gray) # 显示图片
cv2.waitKey(0)
#/////////////////////////2、将灰度图像二值化,设定阈值是100
img_thre = img_gray
cv2.threshold(img_gray, 100, 255, cv2.THRESH_BINARY_INV, img_thre)
cv2.imshow('threshold', img_thre)
cv2.waitKey(0)
#///////////////////////////////////////3、保存黑白图片
cv2.imwrite('thre_res.png', img_thre)
#///////////////////////////////////////4、分割字符
white = [] # 记录每一列的白色像素总和
black = [] # ..........黑色.......
height = img_thre.shape[0]
width = img_thre.shape[1]
white_max = 0
black_max = 0
# 计算每一列的黑白色像素总和
for i in range(width):
s = 0 # 这一列白色总数
t = 0 # 这一列黑色总数
for j in range(height):
if img_thre[j][i] == 255:
s += 1
if img_thre[j][i] == 0:
t += 1
white_max = max(white_max, s)
black_max = max(black_max, t)
white.append(s)
black.append(t)
print(s)
print(t)
arg = False # False表示白底黑字;True表示黑底白字
if black_max > white_max:
arg = True
# 分割图像
def find_end(start_):
end_ = start_ + 1
for m in range(start_ + 1, width - 1):
if (black[m] if arg else white[m]) > (0.95 * black_max if arg else 0.95 * white_max): # 0.95这个参数请多调整,对应下面的0.05
end_ = m
break
return end_
n = 1
start = 1
end = 2
while n < width - 2:
n += 1
if (white[n] if arg else black[n]) > (0.05 * white_max if arg else 0.05 * black_max):
# 上面这些判断用来辨别是白底黑字还是黑底白字
# 0.05这个参数请多调整,对应上面的0.95
start = n
end = find_end(start)
n = end
if end - start > 5:
cj = img_thre[1:height, start:end]
cv2.imshow('caijian', cj)
cv2.waitKey(0)
…
本项目数据集和程序文件:
链接:https://pan.baidu.com/s/1e6TNjVnZKGX-GKzLb8XXgA 提取码:qz51