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Python opencv简单车牌字符分割

Python新视野发表于 2021/09/10 00:19:15 2021/09/10

【摘要】题目描述利用opencv或其他工具编写程序实现简单车牌字符分割。实现过程 import cv2 from pathlib import Path import numpy as np c...

题目描述
利用opencv或其他工具编写程序实现简单车牌字符分割。

实现过程

import cv2  
from pathlib import Path
import numpy as np

current_path = Path.cwd()

#读取图片
image1 = cv2.imread(str(Path(current_path.parent, 'test.png')))
cv2.imshow("image1",image1)

#灰度处理
gray = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
cv2.imshow("gray",gray)

#对灰度处理进行反色
fanse = cv2.bitwise_not(gray)
cv2.imshow("fanse",fanse)

#二值化
_, thresh = cv2.threshold(gray, 130, 255, cv2.THRESH_BINARY)    # 阈值分割，得到二值图
cv2.imshow("binary",thresh)

# 水平投影
thresh1 = thresh.copy()
high, width = thresh1.shape    # 返回高和宽
# 初始化一个跟图像高一样长度的数组，用于记录每一行的黑点个数
arr1 = [0 for n in range(0, high)] 
for row in range(0, high):    # 遍历每行
    for column in range(0, width):    # 遍历每列
        if  thresh1[row, column] == 0:    # 判断该点是否为黑点，0代表黑点
            arr1[row] += 1    # 该行的计数器加一
            thresh1[row, column] = 255    # 将其改为白点，即等于255         
for row  in range(0, high):    # 遍历每一行
    for column in range(0, arr1[row]):    # 从该行应该变黑的最左边的点开始向最右边的点设置黑点
        thresh1[row, column] = 0    # 设置黑点
cv2.imshow('hproject', thresh1)

# 垂直投影
thresh2 = thresh.copy()
high, width = thresh2.shape    # 返回高和宽
# 初始化一个跟图像宽一样长度的数组，用于记录每一列的黑点个数
arr2 = [0 for n in range(0, width)]
for column in range(0, width):    # 遍历每一列 
    for row in range(0, high):    # 遍历每一行
        if  thresh2[row, column] == 0:    # 判断该点是否为黑点，0代表是黑点
            arr2[column] += 1     # 该列的计数器加1
            thresh2[row, column] = 255    # 记录完后将其变为白色，即等于255    
for column in range(0, width):    # 遍历每一列
    for row in range(high - arr2[column], high):    # 从该列应该变黑的最顶部的开始向最底部设为黑点
        thresh2[row, column] = 0    # 设为黑点        
cv2.imshow('vproject', thresh2)

# 矩形分割字符
image = cv2.cvtColor(thresh, cv2.COLOR_GRAY2RGB)
red = (0, 0, 255)
# 设置矩形的各参数
cv2.rectangle(image, (15, 20), (70, 120), red, 2)
cv2.rectangle(image, (80, 20), (135, 120), red, 2)
cv2.rectangle(image, (170, 20), (226, 120), red, 2)
cv2.rectangle(image, (233, 20), (290, 120), red, 2)
cv2.rectangle(image, (300, 20), (355, 120), red, 2)
cv2.rectangle(image, (365, 20), (420, 120), red, 2)
cv2.rectangle(image, (425, 20), (485, 120), red, 2)
cv2.imshow('image', image)

cv2.waitKey()
cv2.destroyAllWindows()

  
 
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