How to read & decode Secure QR code on Indian Aadhaar Card image

Question

I am trying to extract the complete Aadhar number (12 digits) from the image of an Aadhar card (India)

I am able to identify the region with QR code. To extract the info - I have been looking into python libraries that read and decode Secure QR codes on Indian Aadhaar cards. These 2 libraries seem particularly useful for this use case:

1. pyaadhaar
2. aadhaar-py

I am unable to decode Secure QR code using them on Aadhaar cards. Information on Secure QR code is available here. Please recommend possible resolutions or some other methods to achieve this task

Here is my code for decoding secure QR code using these libraries. Python version: 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)

Here are the issues I am facing with these libraries:

1. pyaadhaar: Secure QR code decoding code, tries to convert base10 string to bytes and fails. NOTE: For Old QR Code format of Aadhaar card, pyaadhaar library works well, this issue only occurs for Secure QR code. Stacktrace below:

   File "/home/piyush/libs/py38/lib/python3.8/site-packages/pyaadhaar/deocde.py", line 23, in __init__
   bytes_array = base10encodedstring.to_bytes(5000, 'big').lstrip(b'\x00')
   

   AttributeError: 'str' object has no attribute 'to_bytes'

2. aadhaar-py: Secure QR decoding fails cause it is unable to validate integer received from QR code. Stacktrace below:

   Traceback (most recent call last): File "/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py", line 55, in init self.decompressed_byte_array = zlib.decompress(self.byte_array, wbits=16+zlib.MAX_WBITS) zlib.error: Error -3 while decompressing data: incorrect header check During handling of the above exception, another exception occurred:

   Traceback (most recent call last): File "aadhaarQRCode.py", line 52, in secure_qr = AadhaarSecureQR(integer_scanned_from_qr) File "/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py", line 57, in init raise MalformedIntegerReceived('Decompression failed, please send a valid integer received from QR code') aadhaar.exceptions.MalformedIntegerReceived: Decompression failed, please send a valid integer received from QR code

Answer 1

I think I have identified two issues:

• The quality of the posted sample image is not good enough.
• The posted sample is just an example, and not a real "Secure QR code", but just an example (isSecureQR returns false).

Resizing the input by a factor of 2 allows reading the QR code:

Reading, resizing and saving as a new image:

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)

---

Complete code sample:

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]))

---

Output:

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

As you can see, the information is readable.

---

I don't know the reason for the error messages.
I am using Python 3.6 and Windows 10, and there are no errors.

---

Update:

I think I found a good QR sample here:

You may use the following stages for reading and decoding the QR code:

• Read the image and convert to Grayscale:

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

• Decode the QR image using pyzbar:

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

The output is:

qrData = b'2374971804270526477833002468783965837992554564899874087591661303561346432389832047870524302186901344489362368642972767716416349990805756094923115719687656090691368051627957878187788907419297818953295185555346288172578594637886352753543271000481717080003254556962148594350559820352806251787713278744047402230989238559317351232114240089849934148895256488140236015024800731753594740948640957680138566468247224859669467819596919398964809164399637893729212452791889199675715949918925838319591794702333094022248132120531152523331442741730158840977243402215102904932650832502847295644794421419704633765033761284508863534321317394686768650111457751139630853448637215423705157211510636160227953566227527799608082928846103264491539001327407775670834868948113753614112563650255058316849200536533335903554984254814901522086937767458409075617572843449110393213525925388131214952874629655799772119820372255291052673056372346072235458198199995637720424196884145247220163810790179386390283738429482893152518286247124911446073389185062482901364671389605727763080854673156754021728522287806275420847159574631844674460263574901590412679291518508010087116598357407343835408554094619585212373168435612645646129147973594416508676872819776522537778717985070402222824965034768103900739105784663244748432502180989441389718131079445941981681118258324511923246198334046020123727749408128519721102477302359413240175102907322619462289965085963377744024233678337951462006962521823224880199210318367946130004264196899778609815012001799773327514133268825910089483612283510244566484854597156100473055413090101948456959122378865704840756793122956663218517626099291311352417342899623681483097817511136427210593032393600010728324905512596767095096153856032112835755780472808814199620390836980020899858288860556611564167406292139646289142056168261133256777093245980048335918156712295254776487472431445495668303900536289283098315798552328294391152828182614909451410115516297083658174657554955228963550255866282688308751041517464999930825273776417639569977754844191402927594739069037851707477839207593911886893016618794870530622356073909077832279869798641545167528509966656120623184120128052588408742941658045827255866966100249857968956536613250770326334844204927432961924987891433020671754710428050564671868464658436926086493709176888821257183419013229795869757265111599482263223604228286513011751601176504567030118257385997460972803240338899836840030438830725520798480181575861397469056536579877274090338750406459700907704031830137890544492015701251066934352867527112361743047684237105216779177819594030160887368311805926405114938744235859610328064947158936962470654636736991567663705830950312548447653861922078087824048793236971354828540758657075837209006713701763902429652486225300535997260665898927924843608750347193892239342462507130025307878412116604096773706728162016134101751551184021079984480254041743057914746472840768175369369852937574401874295943063507273467384747124843744395375119899278823903202010381949145094804675442110869084589592876721655764753871572233276245590041302887094585204427900634246823674277680009401177473636685542700515621164233992970974893989913447733956146698563285998205950467321954304'

isSecureQR = (isSecureQr(qrData)) returns True.

• Decode qrData using pyaadhaar:

   secure_qr = AadhaarSecureQr(int(qrData))
   decoded_secure_qr_data = secure_qr.decodeddata()
  

---

Complete code sample:

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)

---

Output:

{'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'}

---

Your original code is also working with the above image:

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 2

For anyone who needs to extract a clean QR code ROI before actually decoding it, here's a simple approach to extract the QR code using thresholding, morphological operations, and contour filtering.

1. Obtain binary image. Load image, grayscale, Gaussian blur, Otsu's threshold

2. Connect individual QR contours. Create a rectangular structuring kernel with cv2.getStructuringElement() then perform morphological operations with cv2.MORPH_CLOSE.

3. Filter for QR code. Find contours and filter using contour approximation, contour area, and aspect ratio.

---

Here's the image processing pipeline

Load image, grayscale, Gaussian blur, then Otsu's threshold to get a binary image

Now we create a rectangular kernel and morph close to combine the QR code into one contour

We find contours and filter for the QR code using contour area, contour approximation, and aspect ratio. The detected QR code is highlighted in green

Extracted ROI

Code

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()     

Answer 3

Thanks for posting the question. I am the author of aadhaar-py, the code raises an exception because the data passed to the lib cannot be parsed. It has to be of a certain type in order for it to be parsable. Please refer the following link for an example: https://uidai.gov.in/te/ecosystem-te/authentication-devices-documents-te/qr-code-reader-te.html

If you scan the qr code present on the page and pass the data received to the lib, you'll receive the extracted data. P.S.: The Lib has been revamped with a new API. Be sure to check it out :) https://pypi.org/project/aadhaar-py/

Answer 4

I am the author of pyaadhaar library . The secure qr actually have binary encoding with data in xml format. Now the qr you provided not in that format. So it's throwing error while decoding. Try with physical copy of aadhar card.

If you are interested in the decoding technique of aadhaar qr, go through this pdf

UIDAI Secure Qr Specification.pdf