用python和opencv写一个汽车车牌识别系统

要实现汽车车牌识别系统，我们需要用到Python和OpenCV库。下面是一个简单的实现步骤：

1. 导入所需库

import cv2
import numpy as np
import pytesseract

2. 加载图像并进行预处理

# 加载图像
img = cv2.imread('car.jpg')

# 灰度化
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 高斯模糊
blur = cv2.GaussianBlur(gray, (5, 5), 0)

# 边缘检测
edged = cv2.Canny(blur, 30, 150)

3. 查找车牌区域

# 查找轮廓
contours, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# 排序轮廓
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]

# 查找车牌轮廓
screenCnt = None
for c in contours:
    # 计算轮廓周长
    peri = cv2.arcLength(c, True)
    # 近似轮廓
    approx = cv2.approxPolyDP(c, 0.02 * peri, True)

    # 判断是否为矩形
    if len(approx) == 4:
        screenCnt = approx
        break

4. 透视变换

# 透视变换
pts = screenCnt.reshape(4, 2)
rect = np.zeros((4, 2), dtype="float32")

# 左上点
s = pts.sum(axis=1)
rect[0] = pts[np.argmin(s)]

# 右下点
rect[2] = pts[np.argmax(s)]

# 计算右上和左下点
diff = np.diff(pts, axis=1)
rect[1] = pts[np.argmin(diff)]
rect[3] = pts[np.argmax(diff)]

# 计算变换矩阵
width, height = 300, 70
dst = np.array([[0, 0], [width, 0], [width, height], [0, height]], dtype="float32")
M = cv2.getPerspectiveTransform(rect, dst)

# 应用透视变换
warped = cv2.warpPerspective(img, M, (width, height))

5. 车牌字符分割

# 灰度化
gray = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)

# 二值化
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]

# 查找轮廓
contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# 创建字符位置列表
letter_image_regions = []

# 遍历轮廓
for contour in contours:
    # 计算轮廓周长
    (x, y, w, h) = cv2.boundingRect(contour)

    # 根据字符尺寸创建限制
    if w / h > 1.25:
        # 取字符左半部分
        half_width = int(w / 2)
        letter_image_regions.append((x, y, half_width, h))
        letter_image_regions.append((x + half_width, y, half_width, h))
    else:
        letter_image_regions.append((x, y, w, h))

# 根据X坐标排序字符位置列表
letter_image_regions = sorted(letter_image_regions, key=lambda x: x[0])

6. OCR识别

# 初始化OCR引擎
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

# 创建空字符串保存识别的字符
plate_text = ''

# 遍历字符位置列表
for letter_bounding_box in letter_image_regions:
    # 提取字符图像
    x, y, w, h = letter_bounding_box
    letter_image = gray[y - 2:y + h + 2, x - 2:x + w + 2]

    # 二值化
    _, letter_image = cv2.threshold(letter_image, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)

    # 调整大小
    letter_image = cv2.resize(letter_image, (28, 28))

    # 执行OCR识别
    letter = pytesseract.image_to_string(letter_image, config='--psm 10')
    plate_text += letter

7. 输出结果

print("车牌号码为：", plate_text)

以上就是一个简单的汽车车牌识别系统的实现步骤，可以根据实际需求进行调整和优化。