车牌识别opencv_基于OpenCV 的车牌识别代码

以下是一个基于OpenCV的车牌识别代码的示例，供您参考：

import cv2
import numpy as np

# 读取图像并进行预处理
img = cv2.imread('car_plate.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5, 5), 0)
edge = cv2.Canny(blur, 50, 150)

# 车牌定位
contours, hierarchy = cv2.findContours(edge, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
    area = cv2.contourArea(cnt)
    if 1000 < area < 100000:
        rect = cv2.minAreaRect(cnt)
        box = cv2.boxPoints(rect)
        box = np.int0(box)
        cv2.drawContours(img, [box], 0, (0, 255, 0), 2)

# 字符分割
plate = img[box[1][1]:box[0][1], box[1][0]:box[2][0]]
gray_plate = cv2.cvtColor(plate, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray_plate, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
    x, y, w, h = cv2.boundingRect(cnt)
    if h / w > 2 and h / w < 5:
        cv2.rectangle(plate, (x, y), (x + w, y + h), (0, 255, 0), 2)
        roi = thresh[y:y + h, x:x + w]
        
        # 字符识别
        # 这里可以使用SVM、神经网络等模型进行分类识别
        
# 显示结果
cv2.imshow('plate', plate)
cv2.waitKey(0)
cv2.destroyAllWindows()

需要注意的是，以上代码只是一个简单的示例，实际的车牌识别系统需要根据实际情况进行调整和优化，才能获得较好的识别效果。