OCR, or optical character recognition, is the method by which text from an image can be converted into a text format that can be read by a computer. For instance, when you scan a document such as a receipt or form, the data is stored as an image file on your computer.
The image file cannot be opened in a text editor, searched, or the number of words counted. Yet OCR can take that image and turn it into a text document, so that the information it contains may be saved as textual data.
Why is OCR Software?
It is common practice for businesses to rely on printed materials as a primary source of incoming information. Paperwork such as invoices, contracts, and forms are often used in business. It takes a lot of time and space to store and organize these massive amounts of paperwork.
Scanning the document into an image presents obstacles, yet paperless document management is the way to go. It’s often time-consuming and laborious because it involves human involvement.
Furthermore, when this content is digitized, image files are produced with the text embedded in it. Word processing programs do not work properly with images containing text.
As a solution, optical character recognition (OCR) technology transforms digital photographs of text into textual information that may then be processed by various types of business software.
Then, the information can be used for analysis, procedure automation, and productivity enhancements.
What are the Benefits of OCR?
There are many varieties of OCR technologies, and data scientists categorize them according to their specific functions. Several instances are listed below.
Simple Optical Character Recognition Software
A basic OCR engine will do its job by keeping a library of pre-existing typeface and text picture patterns. The OCR program compares character by character how a text image looks to what is stored in its database using pattern-matching algorithms.
Word-by-word matching is known as optical word recognition. Since there is a practically infinite number of font and handwriting styles, it is impossible to capture and store every single kind in the database, making this method insufficient.
Intelligent Character Recognition Software
Intelligent character recognition (ICR) technology is used by today’s OCR systems to read the text in the same way a human would. They employ sophisticated techniques to teach computers to mimic human behavior using machine learning programs.
A machine learning system known as a neural network does the multi-layered analysis of the text by continually analyzing the image. It analyzes the image at multiple layers, looking for things like curves, lines, junctions, and loops, then aggregates the data to come up with a single conclusion.
In most cases, ICR analyses the photos one character at a time, yet the entire procedure still only takes a few seconds to complete.
Intelligent Word Recognition
In contrast to ICR, which processes individual characters in an image, intelligent word recognition systems process entire word pictures.
Optical Mark Recognition
Using the use of optical mark recognition, we can decipher linguistic symbols like logos and watermarks embedded in paper documents.
What is OCR Used For?
Here are a few examples of how OCR is typically put to use:
Loan documents, deposit checks, and other banking-related paperwork are processed and verified with the use of OCR. Thanks to this check, we’ve been able to reduce instances of fraud and increase the safety of online transactions.
Such a startup is BlueVine, which uses financial technology to lend to small and medium-sized enterprises. As part of the COVID-19 relief stimulus package, it leveraged Amazon Textract, a cloud-based OCR tool, to create a software that allows small companies in the United States to apply for and receive Paycheck Protection Program (PPP) loans in record time.
BlueVine assisted thousands of firms in obtaining funding thanks to Amazon Textract’s automated processing and analysis of tens of thousands of PPP forms per day, thereby saving over 400,000 jobs.
OCR is used in the healthcare business to process patient records such as therapy, testing, hospital records, and insurance payments. In healthcare settings, OCR can be used to maintain records up to date while also improving efficiency and cutting down on human labor.
For instance, the nib Group handles medical claims for over a million Australians every day. The nib app allows users to submit medical bill images. With the help of Amazon Textract, these photos may be processed automatically, speeding up the claims-approval process.
OCR is used by logistics organizations so that package labels, invoices, and receipts can all be kept track of in one place. To streamline its SAP invoicing process, the Foresight Group, for one, relies on Amazon’s Textract.
Foresight’s staff had to manually enter the data from these business documents into numerous accounting systems, which was a time-consuming and error-prone process.
As a result of integrating Amazon Textract, Foresight software is able to read characters more precisely in a wide variety of layouts, leading to greater productivity in the workplace.
Digital images of physical documents, such as a scanned paper document, can have text characters identified using optical character recognition (OCR) technology.
The foundation of optical character recognition (OCR) is analyzing document text and converting it into machine-readable code. The term “optical character recognition” (OCR) can also be used to refer to text recognition.