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.

Note: Catalyst does not store any of the files you upload in its systems. The documents you upload are used for one-time processing only. They are not used for ML model training purposes either. Catalyst components are fully compliant with all applicable data protection and privacy laws.

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.

Note: Document Processing is only relevant to Indian users and is only available in the IN DC. This feature will not be available to users accessing from the EU or US data centers. Users outside of India from the other DCs can access the general OCR component to read and process textual content.

You must provide the path to the image files of the front and back of the Aadhaar card using the keys aadhaarFront and aadhaarBack, as shown in the code below.

Note: The option to pass the languages present in an Aadhaar card has now been deprecated. Identity Scanner will now automatically identify the languages in an Aadhaar card and process it. The Java SDK code snippet will be updated accordingly soon.

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

Note: The variables should be declared only in following order: aadhaarFront, aadhaarBack, languageCode

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.

Ensure the following packages are imported:

Copiedimport com.zc.component.ml.ZCContent;
import com.zc.component.ml.ZCLine;
import com.zc.component.ml.ZCML;
import com.zc.component.ml.ZCParagraph;
CopiedFile aadhaarFront = new File("/Users/amelia-421/Desktop/myAadhaar1.jpg"); //Specify the file path of the front side image of the Aadhaar card
File aadhaarBack = new File("/Users/amelia-421/Desktop/myAadhaar2.jpg"); //Specify the file path of the back side image of the Aadhaar card
String languageCode = "eng,tam"; //Set the languages
ZCContent ocrContent = ZCML.getInstance().getContentForAadhaar(aadhaarFront,aadhaarBack , languageCode); //Call getContent() with the file object to get the detected text in ZCContent object
//To get individual paragraphs
List <ZCParagraph> paragraphs = ocrContent.getParagraphs();
for(ZCParagraph paragraph : paragraphs){
//To get individual lines in the paragraph
	List<ZCLine> paraLines = paragraph.lines;    
	for(ZCLine line : paraLines){      
//To get individual words in the line  
		String[] words = line.words;        
		String text = line.text;  //Raw line text
	}    
	String text = paragraph.text; //Returns the raw paragraph text
}
String text = ocrContent.text; //Returns the raw image text

API Documentation: OCR Aadhaar- API

Node.js SDK: OCR Aadhaar- Node.js SDK