Introduction
Imagine you could control your data. With Optical Character Recognition (OCR), you can. OCR technology is designed to turn digital images of text into machine-readable text. This means you can extract the text from images, PDFs, and scanned documents giving you back control of your data.
Think about all the ways this could benefit you: You could digitize your handwriting text, Invoices, Payroll data, Contact details, Client data, etc. The possibilities are endless. In this article, we’ll show you how to get started with OCR and how to make the most of its power.
What Is Optical Character Recognition (OCR)?
Optical character recognition, or OCR, is a process by which a computer recognizes and interprets the text in digital images and scanned documents. This can be anything from a receipt to an official document.
OCR technology has been around for a while, but it’s only recently with the impressive improvements in deep learning become accessible to and easy to use by us as users. With the right software, you can now have the images, PDFs and scanned files converted into text that you can edit, save and share. This is a powerful tool for anyone who needs to take control of their data.
How OCR Improves Data Efficiency
OCR software can convert scanned or photographed text into editable text, making it easier and faster to access and use that data. Imagine having to type in or retype all the data you’ve collected from your customer surveys, field notes or research interviews! The process will be much more complicated if you try to extract tables and handwritten ones. That’s where OCR comes in handy it can quickly convert all that text into an organized, searchable and retrievable format like excel sheet, XML, JSON, etc.
Not only does this improve data efficiency, but it also gives you the freedom to use that data however you please. And because the text is editable, you can easily correct any mistakes or spelling errors.
One example of OCR software is AlgoDocs. It is a web-based platform that can achieve reliable and accurate data extraction and can extract handwritten and printed tables and text. Their developed AI-powered OCR engine can handle low-quality files. AlgoDocs can efficiently extract handwritten and printed tables regardless of their complicity and available filters allow the extraction of multipage tables as well ( see Figures 1 and 2 as an example).
Figure1. Sample of low-quality handwritten image processed by AlgoDocs.
Figure2. The extracted table from the scanned handwritten file using AlgoDocs.
How to use AlgoDocs?
First of all, AlgoDocs offers easy-to-follow articles and Video Tutorials that demonstrate how easily its friendly interfaces and functionalities can be used. In general, the wanted data such as text, tables, and handwriting can be extracted through the following steps:
- Select one of the predefined extractors or create a new one by uploading a sample document.
- Select the data type you want to extract, i.e., add an extracting rule in the rules editor.
- Next, click the ‘Extract’ button. At this point, available filters also can be applied if you are willing to format the extracted data.
- Finally, select extraction format, i.e., export to the desired format such as Excel, JSON, or XML or directly to other software.
That is it !!, now you can upload as many files as you have and AlgoDocs will finalize the work shortly.
Conclusion
OCR can be a powerful tool to help you take control of your data. With OCR, you can convert images of text into digital text that can be edited, searched, and stored more easily. OCR can also be used to extract data from images for further analysis.
OCR is a valuable tool that can save you time and effort in dealing with large amounts of data. If you have a need to convert images of text into digital text, OCR may be the right solution for you. AlgoDocs is accessible anytime, anywhere from all devices. You can try the forever free subscription plan with 50 pages per month. You may check AlgoDocs pricing for paid subscriptions based on your document processing requirements.
