Model AI OCR - Read & Filter Insurance card Information
Challenge
The customer assigns about 200 employees the task of data entry - which is high cost, time consuming and there is still a risk of Human errors in the data entry process.
There are 2 types of documents with a large amount of information to enter: Insurance Card & Bill. They need to find a faster & more cost-effective method for this process.
The customer assigns about 200 employees the task of data entry - which is high cost, time consuming and there is still a risk of Human errors in the data entry process.
There are 2 types of documents with a large amount of information to enter: Insurance Card & Bill. They need to find a faster & more cost-effective method for this process.
Solution
Combine multiple AI Models to create a total solution:
- Use Image Processing to re-edit the image (shooting angle, photography direction, blur, shadow ...)
- Use Object Detect to catch the area containing the information needed
- Read information:
-
- Insurance card: Use OCR to read
- Bill: Use OCR to read both print & handwriting. Use Logo searching to collect & classify data about suppliers information.
Customers demand to collect data that change over time and for different work purposes. As a result, HBLAB proposed different AI models to solve changing problems for customers.
Combine multiple AI Models to create a total solution:
- Use Image Processing to re-edit the image (shooting angle, photography direction, blur, shadow ...)
- Use Object Detect to catch the area containing the information needed
- Read information:
-
- Insurance card: Use OCR to read
- Bill: Use OCR to read both print & handwriting. Use Logo searching to collect & classify data about suppliers information.
Customers demand to collect data that change over time and for different work purposes. As a result, HBLAB proposed different AI models to solve changing problems for customers.
Results
The logo & store name accuracy is 93%, the other information accuracy is 95%-97%.
The AI model built by HBLAB helps to save 20% of the customer's initial data entry, optimize costs & speed up work.
The logo & store name accuracy is 93%, the other information accuracy is 95%-97%.
The AI model built by HBLAB helps to save 20% of the customer's initial data entry, optimize costs & speed up work.