信用卡识别
一、环境配置
from imutils import contours
import numpy as np
import argparse
import cv2
import myutils
ap = argparse.ArgumentParser()
ap.add_argument("-i" , "--image" , required=True ,help ="path to input image" )
ap.add_argument("-t" , "--template" , required=True ,help ="path to template OCR-A image" )
args = vars (ap.parse_args())
FIRST_NUMBER = {
"3" : "American Express" ,
"4" : "Visa" ,
"5" : "MasterCard" ,
"6" : "Discover Card"
}
def cv_show (name,img ):
cv2.imshow(name, img)
cv2.waitKey(0 )
cv2.destroyAllWindows()
二、模板处理:
img = cv2.imread(args["template" ])
cv_show('img' ,img)
ref = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv_show('ref' ,ref)
ref = cv2.threshold(ref, 10 , 255 , cv2.THRESH_BINARY_INV)[1 ]
cv_show('ref' ,ref)
ref_, refCnts, hierarchy = cv2.findContours(ref.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(img,refCnts,-1 ,(0 ,0 ,255 ),3 )
cv_show('img' ,img)
print (np.array(refCnts).shape)
refCnts = myutils.sort_contours(refCnts, method="left-to-right" )[0 ]
digits = {}
for (i, c) in enumerate (refCnts):
(x, y, w, h) = cv2.boundingRect(c)
roi = ref[y:y + h, x:x + w]
roi = cv2.resize(roi, (57 , 88 ))
digits[i] = roi
三、处理输入图像
rectKernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9 , 3 ))
sqKernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5 , 5 ))
image = cv2.imread(args["image" ])
cv_show('image' ,image)
image = myutils.resize(image, width=300 )
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv_show('gray' ,gray)
tophat = cv2.morphologyEx(gray, cv2.MORPH_TOPHAT, rectKernel)
cv_show('tophat' ,tophat)
gradX = cv2.Sobel(tophat, ddepth=cv2.CV_32F, dx=1 , dy=0 ,ksize=-1 )
gradX = np.absolute(gradX)
(minVal, maxVal) = (np.min (gradX), np.max (gradX))
gradX = (255 * ((gradX - minVal) / (maxVal - minVal)))
gradX = gradX.astype("uint8" )
print (np.array(gradX).shape)
cv_show('gradX' ,gradX)
gradX = cv2.morphologyEx(gradX, cv2.MORPH_CLOSE, rectKernel)
cv_show('gradX' ,gradX)
thresh = cv2.threshold(gradX, 0 , 255 ,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1 ]
cv_show('thresh' ,thresh)
thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, sqKernel)
cv_show('thresh' ,thresh)
thresh_, threshCnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = threshCnts
cur_img = image.copy()
cv2.drawContours(cur_img,cnts,-1 ,(0 ,0 ,255 ),3 )
cv_show('img' ,cur_img)
locs = []
for (i, c) in enumerate (cnts):
(x, y, w, h) = cv2.boundingRect(c)
ar = w / float (h)
if ar > 2.5 and ar < 4.0 :
if (w > 40 and w < 55 ) and (h > 10 and h < 20 ):
locs.append((x, y, w, h))
locs = sorted (locs, key=lambda x:x[0 ])
output = []
for (i, (gX, gY, gW, gH)) in enumerate (locs):
groupOutput = []
group = gray[gY - 5 :gY + gH + 5 , gX - 5 :gX + gW + 5 ]
cv_show('group' ,group)
group = cv2.threshold(group, 0 , 255 ,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1 ]
cv_show('group' ,group)
group_,digitCnts,hierarchy = cv2.findContours(group.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
digitCnts = contours.sort_contours(digitCnts,method="left-to-right" )[0 ]
for c in digitCnts:
(x, y, w, h) = cv2.boundingRect(c)
roi = group[y:y + h, x:x + w]
roi = cv2.resize(roi, (57 , 88 ))
cv_show('roi' ,roi)
scores = []
for (digit, digitROI) in digits.items():
result = cv2.matchTemplate(roi, digitROI,cv2.TM_CCOEFF)
(_, score, _, _) = cv2.minMaxLoc(result)
scores.append(score)
groupOutput.append(str (np.argmax(scores)))
四、得出结果
cv2.rectangle(image, (gX - 5 , gY - 5 ),(gX + gW + 5 , gY + gH + 5 ), (0 , 0 , 255 ), 1 )
cv2.putText(image, "" .join(groupOutput), (gX, gY - 15 ),cv2.FONT_HERSHEY_SIMPLEX,0.65 , (0 , 0 , 255 ), 2 )
output.extend(groupOutput)
cv2.imshow("Image" , image)
print ("Credit Card Type: {}" .format (FIRST_NUMBER[output[0 ]]))
print ("Credit Card #: {}" .format ("" .join(output)))
cv2.waitKey(0 )
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