Capture and process electronic identity cards

May 22, 2024
 Id-scanning

Efficient and secure ID verification is crucial for various industries, from banking to travel. This blog explores a use case involving the capture and processing of a Belgian electronic identity card for archiving purposes, followed by the extraction of the cardholder’s information into structured fields.

The Process of Automated ID Verification

Imagine a scenario where a user needs to verify their identity to access a service, such as opening a bank account online. Traditionally, this process might involve manually entering details and uploading copies of their ID. However, by leveraging Dynamsoft’s data scanning and capture SDKs, this process can be automated and simplified. The steps involved are:

  1. Capturing the ID Image
  2. Cropping the ID Section
  3. Reading the Data Matrix Code
  4. Extracting and Parsing MRZ Text

document-scanning-data-capture

Step 1: Capturing the ID Image

The first step involves taking a picture of the ID, which can be done using a smartphone or a scanner.

Mobile Web Capture: This tool can be integrated into web apps to facilitate image capture from mobile cameras, even in varying lighting conditions. It provides real-time feedback to users for optimal image quality.

Dynamic Web TWAIN: A browser-based document scanning SDK that supports a wide range of scanner drivers, including TWAIN, WIA, ICA, SANE, and eSCL. It enables users to scan documents directly from within Chrome, Firefox, Edge, and other mainstream browsers.

Step 2: Cropping the ID Section

Once the image is captured, the next step is to isolate the ID from the rest of the image. This can be achieved using Dynamsoft Document Normalizer. The SDK offers functionalities to detect and crop the ID section from the image. Using contour detection and edge detection algorithms, it can accurately identify and extract the ID from the image. Dynamsoft Document Normalizer also provides a set of image filters to help clean up the images.

Capturing-ID-Image

The Benefits of Cropping the ID Section Before Recognizing the Barcode and MRZ

Improved Accuracy

By isolating the ID section, recognition algorithms can focus specifically on the area containing the barcode and MRZ, reducing the likelihood of errors caused by extraneous information in the background.

Faster Processing

With a smaller, more relevant section of the image to analyze, the recognition process becomes faster. The software does not need to process the entire image, leading to quicker results.

Step 3: Reading the Barcode

The Belgian electronic identity card includes a Data Matrix code that contains encoded personal information. To read this barcode, we can use Dynamsoft Barcode Reader, a barcode image-processing library designed for the most demanding scenarios. Dynamsoft Barcode Reader can decode various barcode formats, including Data Matrix codes, QR codes, and PDF417, commonly found on IDs.

working-with-clean-well-cropped-image

Step 4: Extracting and Parsing MRZ Text

The Machine Readable Zone (MRZ) on IDs contains critical information encoded in a standardized format. To extract text from the MRZ, we utilize Optical Character Recognition (OCR) technology. Dynamsoft Label Recognizer is highly effective for this purpose. It comes with a pre-trained data model to recognize MRZ fonts and extract text accurately.

After extracting the text, the next task is to parse this information into structured fields. The MRZ format is standardized, making it relatively straightforward to split the text into fields such as document type, issuing country, document number, birth date, expiration date, and personal details. This parsing can be implemented using Dynamsoft Code Parser.

Technology Stack

  • Mobile Web Capture or Dynamic Web TWAIN: For capturing high-quality images.
  • Dynamsoft Document Normalizer: For image processing and cropping the ID section.
  • Dynamsoft Barcode Reader: For reading and decoding barcodes.
  • Dynamsoft Label Recognizer: For extracting text from the MRZ.
  • Dynamsoft Code Parser: For parsing the extracted text into structured fields.

Getting Started

By combining these advanced technologies, we can create a seamless and efficient ID capture process. This automated solution not only enhances user experience by reducing manual input but also improves security by minimizing human errors.

Discuss with our experts on how to harness the power of integrating various technologies to solve real-world problems.

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