在这个Python OpenCV项目中，我如何让Tesseract读取车牌？

Question

我的OpenCV代码运行良好。它找到了车牌，用轮廓提取出了它的黑白版本，然后当我把它传给pytesseract时，它不会读任何字母。我跟踪了该程序的每一行代码，OpenCV运行良好，但是pytesseract不能从图像中提取文本。没有错误，它只是不读取任何文本。车牌是我的。

import cv2
# pip install imutils
import imutils
import pytesseract

pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files (x86)\Tesseract-OCR\tesseract.exe'

# Read the image file
image = cv2.imread('LP.jpg')
# image = imutils.resize(image, width=500)

# Convert to Grayscale Image
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Removes Noise
gray_image = cv2.bilateralFilter(gray_image, 11, 17, 17)

# Canny Edge Detection
canny_edge = cv2.Canny(gray_image, 100, 200)

# Find contours based on Edges
# The code below needs an - or else you'll get a ValueError: too many values to unpack (expected 2) or a numpy error
_, contours, new = cv2.findContours(canny_edge.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:30]

# # Initialize license Plate contour and x,y coordinates
contour_with_license_plate = None
license_plate = None
x = None
y = None
w = None
h = None

# Find the contour with 4 potential corners and create a Region of Interest around it
for contour in contours:
    # Find Perimeter of contour and it should be a closed contour
    perimeter = cv2.arcLength(contour, True)
    approx = cv2.approxPolyDP(contour, 0.02 * perimeter, True)
    # This checks if it's a rectangle
    if len(approx) == 4:
        contour_with_license_plate = approx
        x, y, w, h = cv2.boundingRect(contour)
        license_plate = gray_image[y:y + h, x:x + w]
        break


# # approximate_contours = cv2.drawContours(image, [contour_with_license_plate], -1, (0, 255, 0), 3)

# Text Recognition
text = pytesseract.image_to_string(license_plate, lang='eng')
print(text)
# Draw License Plate and write the Text
image = cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 3)
image = cv2.putText(image, text, (x-100, y-50), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 255, 0), 6, cv2.LINE_AA)

print("License Plate: ", text)

cv2.imshow("License Plate Detection", image)
cv2.waitKey(0)

Answer 1

这是我的部分答案，也许你可以完善它。

将自适应阈值按位不操作应用于license_plate变量。

结果将是：

现在如果你读到它：

txt = pytesseract.image_to_string(bnt, config="--psm 6")  
print(txt)

结果：

277 BOY

不幸的是Q被识别为O。

代码：（只需将文本识别注释部分替换为以下内容）

thr = cv2.adaptiveThreshold(license_plate, 252, cv2.ADAPTIVE_THRESH_MEAN_C,
                            cv2.THRESH_BINARY_INV, 91, 93)
bnt = cv2.bitwise_not(thr)
txt = pytesseract.image_to_string(bnt, config="--psm 6")
print(txt)