运用python车牌字符识别完整代码(不需要训练集)
时间: 2023-09-15 19:24:16 浏览: 40
以下是基于OpenCV和Tesseract OCR库的Python车牌字符识别完整代码:
```python
import cv2
import pytesseract
# 读取图片
img = cv2.imread('car_plate.jpg')
# 转换为灰度图像
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 进行形态学操作,提高图像质量
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
gray = cv2.morphologyEx(gray, cv2.MORPH_CLOSE, kernel)
# 进行二值化处理
ret, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
# 查找轮廓
contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# 获取车牌轮廓
plate_contour = None
for contour in contours:
x, y, w, h = cv2.boundingRect(contour)
if w > h:
if (w / h > 2.5 and w / h < 4.0) and (w > img.shape[1] * 0.1 and w < img.shape[1] * 0.9) and (
h > img.shape[0] * 0.1 and h < img.shape[0] * 0.5):
plate_contour = contour
break
if plate_contour is not None:
# 获取车牌图像
x, y, w, h = cv2.boundingRect(plate_contour)
plate_img = img[y:y + h, x:x + w]
# 将车牌图像转换为灰度图像
plate_gray = cv2.cvtColor(plate_img, cv2.COLOR_BGR2GRAY)
# 进行二值化处理
ret, plate_binary = cv2.threshold(plate_gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
# 进行形态学操作,提高图像质量
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
plate_binary = cv2.morphologyEx(plate_binary, cv2.MORPH_CLOSE, kernel)
# 进行字符识别
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
result = pytesseract.image_to_string(plate_binary, lang='chi_sim')
# 输出结果
print(result)
else:
print('未找到车牌')
```
注意:此代码依赖于Tesseract OCR库,需要先在计算机上安装该库,并将`tesseract_cmd`变量设置为Tesseract二进制文件的路径。