Identity Scanner

Identity Scanner is a Zia AI-driven component that enables you to perform secure identity checks on individuals and documents by scanning and processing various ID proofs or official documents. It is a comprehensive suite that incorporates multiple functionalities divided into two major categories- E-KYC and Document Processing.

Aadhaar

The AADHAAR model is a part of the Document Processing feature that enables you to process Indian Aadhaar cards as identity proof documents. This enables you to extract fields of data from an Indian Aadhaar card using an advanced OCR technology. The response will return the parameters recognized from the Aadhaar card, along with confidence scores for each recognition that determine their accuracy.

You must provide the path to the image files of the front and back of the Aadhaar card to the open() method, as shown in the code below. This opens both the files and returns the respective file objects as a response. The zia reference used below is already defined in the component instance page.

Identity Scanner will now automatically identify the languages in an Aadhaar card and process it. You can temporarily pass the languages as shown in the code below. You must pass English and the relevant regional language. For example, if you are from Tamil Nadu, you must pass tam and eng as the languages. You can check the list of languages and language codes from the API documentation.

Allowed file formats: .jpg, .jpeg, .png, .bmp, .tiff, .pdf
File size limit: 15 MB

The response contains the parameters recognized in the Aadhaar card such as the card holder’s name, address, gender, Aadhaar card number assigned to respective keys. The response also shows a confidence score in the range of 0 to 1 for each of the recognized values.

    

        
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         img = open('sample.jpg', 'rb')
img2 = open('sample2.jpg', 'rb')
result = zia.extract_aadhaar_characters(img, img2, language='eng,tam')

    

A sample response is shown below :

    

        
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         {
  text: "{
      "address":{
            "prob":0.5,"value":"C/O Rainbow, xxxx STREET, xxxx- 0000"
                       },
       "gender":{
             "prob":0.8,"value":"MALE"
                      },
       "dob":{
              "prob":0.8,
               "value":"08/09/2001"
                  },
        "name":{
               "prob":0.6,
               "value":"Ram Singh"
                     },
         "aadhaar":{
                "prob":0.8,
                "value":"4000 0000 0000"
                     }
             }"
}