如何在印度Aadhaar卡图像上读取和解码安全QR码

Question

我正试图从Aadhar卡(印度)的图像中提取完整的Aadhar数(12位数字)。

​

​

我能够用QR代码识别该区域。为了提取这些信息，我一直在研究阅读和解码印度Aadhaar卡上安全的QR代码的python库。对于这个用例，这两个库似乎特别有用：

1. 皮亚达
2. 阿达尔-比

我无法在Aadhaar卡上使用它们解码安全的QR代码。有关安全QR代码的信息可在这里获得。 请推荐可能的解决方案或其他一些方法来完成此任务

下面是我使用这些库解码安全QR代码的代码。Python版本: 3.8

from pyaadhaar.utils import Qr_img_to_text, isSecureQr
from pyaadhaar.deocde import AadhaarSecureQr
from pyaadhaar.deocde import AadhaarOldQr

qrData = Qr_img_to_text(sys.argv[1])
print(qrData)

if len(qrData) == 0:
    print(" No QR Code Detected !!")
else:
    isSecureQR = (isSecureQr(qrData[0]))
    if isSecureQR:
        print("Secure QR code")
        try:
            obj  = AadhaarSecureQr(qrData[0])
        except:
            print("Try aadhaar-py library")
            from aadhaar.qr import AadhaarSecureQR
            integer_scanned_from_qr = 123456
            # secure_qr = AadhaarSecureQR(integer_scanned_from_qr)
            secure_qr = AadhaarSecureQR(int(qrData[0]))
            decoded_secure_qr_data = secure_qr.extract_data()
            print(decoded_secure_qr_data)

以下是我在这些图书馆所面临的问题：

1. pyaadhaar:安全的QR码解码代码，尝试将base10字符串转换为字节，但失败。注意：为旧QR码格式的Aadhaar卡，pyaadhaar库工作良好，此问题只发生在安全QR代码上。Stacktrace如下： 文件"/home/piyush/libs/py38/lib/python3.8/site-packages/pyaadhaar/deocde.py"，第23行，在__init__ bytes_array = base10encodedstring.to_bytes(5000，'big').lstrip(b'\x00')中 AttributeError: 'str' object has no attribute 'to_bytes'
2. aadhaar-py:安全QR解码失败，因为它无法验证从QR代码接收到的整数。Stacktrace如下： 回溯(最近一次调用)：文件"/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py"，第55行，在init self.decompressed_byte_array = zlib.decompress(self.byte_array，wbits=16+zlib.MAX_WBITS) zlib.error: Error -3中，同时解压缩数据:在处理上述异常时不正确的标头检查，发生了另一个异常：

回溯(最近一次调用)：文件"aadhaarQRCode.py"，第52行，在secure_qr = AadhaarSecureQR(integer_scanned_from_qr)文件AadhaarSecureQR第57行，在init send (‘解压失败，请发送从QR代码接收的有效整数’) aadhaar.exceptions.MalformedIntegerReceived:解压缩失败，请发送从QR代码接收的有效整数

Answer 1

谢谢你贴出这个问题。我是aadhaar-py的作者，代码会引发异常，因为传递给lib的数据不能被解析。它必须是某种类型的，才能被解析。有关示例，请参阅以下链接：https://uidai.gov.in/te/ecosystem-te/authentication-devices-documents-te/qr-code-reader-te.html

如果扫描页面上的qr代码并将收到的数据传递给库，您将收到提取的数据。P.S.：Lib已经用一个新的API进行了改造。请务必检查一下:) https://pypi.org/project/aadhaar-py/

Answer 2

我想我已经指出了两个问题：

• 张贴的样本图像质量不够好。
• 发布的示例只是一个示例，而不是真正的“安全QR代码”，而只是一个示例(isSecureQR返回false)。

通过调整输入因子2的大小，可以读取QR代码：

读取、调整大小和保存为新图像：

import cv2    

image_file_name = 'image.png';

img = cv2.imread(image_file_name, cv2.IMREAD_GRAYSCALE)  # Read image as grayscale.
img2 = cv2.resize(img, (img.shape[1]*2, img.shape[0]*2), interpolation=cv2.INTER_LANCZOS4)  # Resize by x2 using LANCZOS4 interpolation method.

cv2.imwrite('image2.png', img2)

完整代码示例：

import cv2
from pyaadhaar.utils import Qr_img_to_text, isSecureQr
from pyaadhaar.deocde import AadhaarSecureQr
from pyaadhaar.deocde import AadhaarOldQr

image_file_name = 'image.png';

img = cv2.imread(image_file_name, cv2.IMREAD_GRAYSCALE)  # Read image as grayscale.
img2 = cv2.resize(img, (img.shape[1]*2, img.shape[0]*2), interpolation=cv2.INTER_LANCZOS4)  # Resize by x2 using LANCZOS4 interpolation method.

cv2.imwrite('image2.png', img2)

#qrData = Qr_img_to_text(image_file_name)
qrData = Qr_img_to_text('image2.png')

print(qrData[0])

if len(qrData) == 0:
    print(" No QR Code Detected !!")
else:
    isSecureQR = (isSecureQr(qrData[0]))

输出：

BEGIN:VCARD
VERSION:2.1
N:John Doe
TEL;HOME;VOICE:555-555-5555
TEL;WORK;VOICE:666-666-6666
EMAIL:email@example.com
ORG:TEC-IT
URL:http://www.example.com
END:VCARD

如您所见，这些信息是可读的。

我不知道错误信息的原因。

我使用的是Python3.6和Windows 10，没有错误。

更新：

我想我找到了一个很好的QR样本这里

​

​

您可以使用以下阶段来读取和解码QR代码：

• 读取图像并转换为灰度： img = cv2.imread('QR-code.png') gray = cv2.cvtColor(img，cv2.COLOR_BGR2GRAY)
• 使用比兹巴解码QR图像： 从pyzbar.pyzbar导入解码代码=解码(灰色) qrData = code.data

产出如下：

qrData = b'2374971804270526477833002468783965837992554564899874087591661303561346432389832047870524302186901344489362368642972767716416349990805756094923115719687656090691368051627957878187788907419297818953295185555346288172578594637886352753543271000481717080003254556962148594350559820352806251787713278744047402230989238559317351232114240089849934148895256488140236015024800731753594740948640957680138566468247224859669467819596919398964809164399637893729212452791889199675715949918925838319591794702333094022248132120531152523331442741730158840977243402215102904932650832502847295644794421419704633765033761284508863534321317394686768650111457751139630853448637215423705157211510636160227953566227527799608082928846103264491539001327407775670834868948113753614112563650255058316849200536533335903554984254814901522086937767458409075617572843449110393213525925388131214952874629655799772119820372255291052673056372346072235458198199995637720424196884145247220163810790179386390283738429482893152518286247124911446073389185062482901364671389605727763080854673156754021728522287806275420847159574631844674460263574901590412679291518508010087116598357407343835408554094619585212373168435612645646129147973594416508676872819776522537778717985070402222824965034768103900739105784663244748432502180989441389718131079445941981681118258324511923246198334046020123727749408128519721102477302359413240175102907322619462289965085963377744024233678337951462006962521823224880199210318367946130004264196899778609815012001799773327514133268825910089483612283510244566484854597156100473055413090101948456959122378865704840756793122956663218517626099291311352417342899623681483097817511136427210593032393600010728324905512596767095096153856032112835755780472808814199620390836980020899858288860556611564167406292139646289142056168261133256777093245980048335918156712295254776487472431445495668303900536289283098315798552328294391152828182614909451410115516297083658174657554955228963550255866282688308751041517464999930825273776417639569977754844191402927594739069037851707477839207593911886893016618794870530622356073909077832279869798641545167528509966656120623184120128052588408742941658045827255866966100249857968956536613250770326334844204927432961924987891433020671754710428050564671868464658436926086493709176888821257183419013229795869757265111599482263223604228286513011751601176504567030118257385997460972803240338899836840030438830725520798480181575861397469056536579877274090338750406459700907704031830137890544492015701251066934352867527112361743047684237105216779177819594030160887368311805926405114938744235859610328064947158936962470654636736991567663705830950312548447653861922078087824048793236971354828540758657075837209006713701763902429652486225300535997260665898927924843608750347193892239342462507130025307878412116604096773706728162016134101751551184021079984480254041743057914746472840768175369369852937574401874295943063507273467384747124843744395375119899278823903202010381949145094804675442110869084589592876721655764753871572233276245590041302887094585204427900634246823674277680009401177473636685542700515621164233992970974893989913447733956146698563285998205950467321954304'

isSecureQR = (isSecureQr(qrData))返回True。

• 使用qrData pyaadhaar解码： secure_qr = AadhaarSecureQr(int(qrData)) decoded_secure_qr_data = secure_qr.decodeddata()

完整代码示例：

import cv2
from pyzbar.pyzbar import decode
from pyaadhaar.utils import isSecureQr
from pyaadhaar.deocde import AadhaarSecureQr

img = cv2.imread('QR-code.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

code = decode(gray)
qrData = code[0].data

isSecureQR = (isSecureQr(qrData))

if isSecureQR:
    secure_qr = AadhaarSecureQr(int(qrData))
    decoded_secure_qr_data = secure_qr.decodeddata()
    print(decoded_secure_qr_data)

输出：

{'email_mobile_status': '3', 'referenceid': '269720190308114407437', 'name': 'Sumit Kumar', 'dob': '01-01-1984', 'gender': 'M', 'careof': 'C/O Ishwar Chand', 'district': 'East Delhi', 'landmark': '', 'house': 'B-31, 3rd Floor', 'location': '', 'pincode': '110051', 'postoffice': 'Krishna Nagar', 'state': 'Delhi', 'street': 'Radhey Shyam Park Extension', 'subdistrict': 'Gandhi Nagar', 'vtc': 'Krishna Nagar', 'adhaar_last_4_digit': '2697', 'adhaar_last_digit': '7', 'email': 'yes', 'mobile': 'yes'}

您的原始代码也在处理上面的图像：

from pyaadhaar.utils import Qr_img_to_text, isSecureQr

qrData = Qr_img_to_text('QR-code.png')

isSecureQR = (isSecureQr(qrData[0]))

if isSecureQR:
    secure_qr = AadhaarSecureQr(int(qrData[0]))
    decoded_secure_qr_data = secure_qr.decodeddata()
    print(decoded_secure_qr_data)

Answer 3

对于任何需要在实际解码之前提取干净的QR代码ROI的人，这里有一种使用阈值处理、形态操作和轮廓过滤提取QR代码的简单方法。

1. 获得二值图像。 负载图像 灰鳞 高斯模糊 Otsu阈值
2. 连接单个QR轮廓。用cv2.getStructuringElement()创建一个矩形结构内核，然后用cv2.MORPH_CLOSE执行形态运算。
3. 用于QR代码的过滤器. 寻找轮廓和使用等高线近似、等高线面积和纵横比的过滤器.

这是图像处理管道

加载图像，灰度，高斯模糊，然后Otsu的阈值得到二值图像

​

​

现在，我们创建一个矩形内核和形状接近，将QR代码组合成一个轮廓。

​

​

我们利用等高线面积、轮廓近似和高宽比为QR码寻找等高线和滤波器。检测到的QR代码以绿色高亮显示。

​

​

提取ROI

​

​

代码

import cv2
import numpy as np

# Load imgae, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread('1.png')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (7,7), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Morph close
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=1)

# Find contours and filter for QR code using contour area, approximation, and aspect ratio
cnts = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.04 * peri, True)
    x,y,w,h = cv2.boundingRect(approx)
    area = cv2.contourArea(c)
    ar = w / float(h)
    if len(approx) == 4 and area > 1000 and (ar > .85 and ar < 1.3):
        cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 3)
        ROI = original[y:y+h, x:x+w]
        # cv2.imwrite('ROI.png', ROI)

# Display
cv2.imshow('thresh', thresh)
cv2.imshow('close', close)
cv2.imshow('image', image)
cv2.imshow('ROI', ROI)

# Save images
# cv2.imwrite('thresh.png', thresh)
# cv2.imwrite('close.png', close)
# cv2.imwrite('image.png', image)
# cv2.imwrite('ROI.png', ROI)
cv2.waitKey()