opencv实战项目：基于opencv的车牌号码识别

首先，呈上我自己根据代码写的步骤流程，方便记忆，字有点丑，哈哈哈！！！ 好吧，图片看不清，那就上代码

import cv2
import imutils
import numpy as np
import pytesseract
pytesseract.pytesseract.tesseract_cmd = rD:Program FilesTesseract-OCR	esseract.exe

img = cv2.imread(D:/skoda1.png,cv2.IMREAD_COLOR)
img = cv2.resize(img, (600,400) )

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
gray = cv2.bilateralFilter(gray, 13, 15, 15) 

edged = cv2.Canny(gray, 30, 200) 
contours = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(contours)
contours = sorted(contours, key = cv2.contourArea, reverse = True)[:10]
screenCnt = None

for c in contours:
    
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.018 * peri, True)
 
    if len(approx) == 4:
        screenCnt = approx
        break

if screenCnt is None:
    detected = 0
    print ("No contour detected")
else:
     detected = 1

if detected == 1:
    cv2.drawContours(img, [screenCnt], -1, (0, 0, 255), 3)

mask = np.zeros(gray.shape,np.uint8)
new_image = cv2.drawContours(mask,[screenCnt],0,255,-1,)
new_image = cv2.bitwise_and(img,img,mask=mask)

(x, y) = np.where(mask == 255)
(topx, topy) = (np.min(x), np.min(y))
(bottomx, bottomy) = (np.max(x), np.max(y))
Cropped = gray[topx:bottomx+1, topy:bottomy+1]

text = pytesseract.image_to_string(Cropped, config=--psm 11)
print("programming_fevers License Plate Recognition
")
print("Detected license plate Number is:",text)
img = cv2.resize(img,(500,300))
Cropped = cv2.resize(Cropped,(400,200))
cv2.imshow(car,img)
cv2.imshow(Cropped,Cropped)

cv2.waitKey(0)
cv2.destroyAllWindows()

这里由于时间长了，有些api忘记咋用了，就又重新搜索下如下：

开头代码的文件下载方法

总结下吧 感觉前面很基础就利用opencv的基础预处理图像，后面主要是找轮廓进行裁剪字符分割与字符识别。