Passport, KYC Documents, Business Personnel, driver’s licenses, or any ID card is one of the most common documents to verify the identity and authenticity of any individual or Business. To verify every data of the id Card, correctly extracting data is the very crucial and sensitive part, and this process takes time if you do it manually as a human. So, to resolve this issue, the Software Engineer of Docextractor Invented the ID Card Digitization Service.
In this article, I am gonna show you the complete details of how the company uses AI and Deep Learning Technology to Automate data extraction from ID Cards with high accuracy and efficiency.
So, Let’s get started.
What is Data Extraction from ID Cards with AI?
AI Data Extraction from ID Card is the automated process of extracting data from any ID card like a Passport, Office ID Card, or anything. Each and every element of the ID card will be extracted from the card and saved in external databases.
This is a very time-consuming and error-free process. After extracting each and every data, the digital copy will be reviewed by the manual reviewer, though, the accuracy is very high.
Benefits of Data Extraction from ID Cards
1. Each and Every Information Extraction
By using, the Docexractor ID Card digitization service, you can capture each and every data from the ID card and save the data in another storage for further use. All the information from the ID card will be saved in a Normal Text and Numerical Format. Moreover, the extracted data from ID cards can help others with any kind of verification or registration process.
2. High Speed and efficiency
Digitizing ID cards by using Docextractor can save a lot of time and extra costs for businesses and organizations. Basically, it takes a few seconds the scan an ID card and retrieves all data from ID Card, and reduces the processing time. As we know, we have to wait at the front desk while an employee leisurely rewrites the passport data in a worn notebook, or fills out several online forms by manually copy-pasting. But, with the help of the Automated Data Extraction from ID Card, this process is very fast rather than manual entry.
3. Error Free
Sometimes, only copy-pasting data from the ID card, manually, is prone to some errors. But, with help of the AI technology and computational power, the software is able to capture data without many errors. The potential for human error can be reduced by automating repetitive tasks.
4. Save and Integrates Data into any system
Digitized Data of any Document can be easily integrated and saved into any storage. Any extracted data from the ID card can be saved in the other database. For example, a model trained to recognize information from a specific ID card can be deployed on a website where users upload images in a huge volume and extract information. Business or any Organization can integrate their Databases into the Data Extraction Dashboard Panel to save the data in an organized way.
The Main Challenges to Extract Character During ID Card Digitalization
1. Different Designing and Templates of ID Cards
Many organizations or Businesses have different types of ID cards in different fonts and designs and templates, either Small Square or Verticle Rectangle or Horizontal Rectangle and, many more types. That is why there are variations between characters in different fonts and many patterns. In fact, some ID cards are printed in different languages. So, capturing information from scanned documents remains a primary research problem because information with complex symbolism is more troublesome. But, Don’t worry, You will use Docextractor, and we can resolve all of these issues.
2. Orientation of Text
Basically, the ID Cards Scanned document or ID card is parallel to the plane of the sensor. During capturing manually with a camera, we face many have various problems such as orientation and skewness. The Orientation sense of Mobile can recognize if the device is tilted and when it is twisted, they can prohibit clients from taking pictures.
3. The Angle of the Text
Skewness or Angle of the Text in the ID Cards is also captured during the process. If the angle of the Text is very high, it will show some poor inaccurate results. But, by using Docextractor, there are several techniques that we used to overcome this problem such as projection profile, Hough transform, Fourier transform method, and many more.
4. The Visibility of the Screen
The lack of Visibility of the Data of the Images of the ID Card made it very difficult to extract data from any Document. Though, the visibility depends on various factors, say, uneven lighting, contrast, position, and many more The structure and presence of text make image processing challenges. So, to overcome this, you have to process the image before training for data extraction or labeling the ID card. Docexractor uses some filters that highlight text and makes it easier for the model to process the image.
How to Digitalize the ID Card with Docextractor?
Docextractor creates OCR models where you need to upload your data, annotate it, set the model to train, and the captured data will extract and save into your Storage.
Some are the fields are common in ID Cards, such are, First name, Last name, and Date of Birth. That’s why, Docextractor is already made some Templates for the ID card, where the Data will be stored in this format in the Storage.
- Step #1: First, you need to upload the image of the ID Cards into the Docextractor Software and divide all documents into various categories which contain specific repeating fields.
- Step #2: Then, you have to create or select a Template to ease the process of all similar Documents. And, with the help of Automatic Layout Detections, processing them separately
- Step #3: And, in this final stage, Docextractor OCR analyzes and process every data Element of the File several time and Extracted all data in an organized way, and save it into the Storage.
To Sum up here is all about Data Extraction from ID cards. ID Card Digitalization reduces human effort, and the risk of error, and also saves a lot of time. So, I Hope, you have already understood the usage of Deep Learning to Automatic any Manual Work and how it deploys solutions in real-time across multiple applications of any type of Business.