Why OCR for Passports?
Let's check out why you should use Optical Character Recognition for passports. Also look at how it works for passport data.
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Businesses that deal with passports on a daily basis face steep time investments and security concerns. Unless there is some automation in place, these companies are forced to manually handle and process each passport, a solution that does not have scale in mind. Optical Character Recognition (OCR) bridges this gap by identifying and digitizing relevant text, but this poses a whole new set of problems: training and maintenance of a custom passport model are the first that come to mind. Luckily, there is a safe, cost and time effective way to solve these issues.
How OCR Works with Passport Data
Keeping up with vital information plays an essential role in the growth of your business. By using a trained OCR model, you can cut back on the time you waste and organize the information in an efficient manner.
When a client sends a passport to your company, you want to gather the relevant information and get it organized. OCR digitizes the text from a client's passport and gives you a result with the data. You can then organize the information to keep up with your client's needs and goals.
Organizing the Information
Since OCR gives you the text from a passport, you can quickly organize the information and put it into an appropriate file. Double check the data to ensure that it is in the format you want or need. Name your file and then save the data in the appropriate folder or space on your company computer. You can pull up the data when you need information from your client's passport. It also allows you to save essential information for company documents or records.
OCR for passports gives you an easy way to stay up-to-date with data from a passport. It cuts back on the time you waste by manually entering the information so that you can focus on other tasks and the growth of your business.
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Published at DZone with permission of David Hoffman, DZone MVB. See the original article here.
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