effect
First look at the effect
Test results:
Ideas
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Original image to grayscale
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Perform Gaussian filtering, median filtering and denoising on grayscale images
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Use the sobel operator to calculate the gradient (that is, extract the edge). Considering that the words on the license plate are all thin and long, I only use the horizontal gradient here to avoid environmental interference
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Gaussian filtering of the gradient map to remove details
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Convert Binary Graph
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Corrosion once and expand 10 times to connect the license plate into a white color block
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Find the contour with the largest enclosed area, correct the direction, and finally draw
Code
import cv2
import numpy as np #read the
picture
imagePath ='car.jpg'
img = cv2.imread(imagePath) #turn
to grayscale
img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #Gaussian
filter + median filter
img_gaus = cv2.GaussianBlur(img_gray,(3,3),0,0,cv2.BORDER_DEFAULT)
img_median = cv2.medianBlur(img_gaus,3) #Use the
sobel operator to calculate the gradient and only calculate the horizontal direction
#The purpose of turning into a 64-bit float Keep the negative values in the gradient
x = cv2.Sobel(img_median,cv2.CV_64F,1,0,ksize = 3)
gra = cv2.convertScaleAbs(x) #Gaussian
filtering again to remove noise
blurred = cv2.GaussianBlur(gra,(9 , 9), 0)
# turn binary picture
_, = cv2.threshold thresholded (, blurred, 100,255, cv2.THRESH_BINARY)
# cross selected nuclear
kernel1 = cv2.getStructuringElement (cv2.MORPH_CROSS, (3,3))
# corrosion Swell
erode = cv2.erode(thresholded,kernel1,iterations= 1)
dilate = cv2.dilate(erode,kernel1,iterations=10)
#找轮廓
cnt,_ = cv2.findContours(dilate.copy(),cv2.RETR_LIST,cv2.CHAIN_APPROX_NONE)
c = sorted(cnt, key=cv2.contourArea, reverse=True)[0]
rect = cv2.minAreaRect(c)
Box = np.int0(cv2.boxPoints(rect))
#轮廓校正
x1 = np.max(Box[...,0])
x2 = np.min(Box[...,0])
y1 = np.max(Box[...,1])
y2 = np.min(Box[...,1])
new_box= np.array([[x2,y2],[x2,y1],[x1,y1],[x1,y2]])
#展示效果
Final_img = cv2.drawContours(img.copy(), [new_box], -1, (0, 0, 255), 3)
cv2.imshow('License',Final_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.imwrite('tmp.jpg',Final_img)
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