In recent times the world has seen large-scale digitization of businesses and other financial institutions. There is a competition for the best online platforms that provide security as well as remarkable service to customers. Not just that, businesses also get more reach globally through online platforms.
OCR systems are part of this boom in digitization because OCR scanning saves considerable time in the processing of data. It is for this reason that more and more businesses are demanding OCR technology as part of their system. According to KBV research, the OCR market is going to grow to 12.6 billion dollars by 2025.
How OCR Compliance Makes Processes Easier?
Since advancements in technology have made it a battle between digital businesses, the need to adopt the trending solutions is increasing on a daily basis. Processes like data entry used to be very time-consuming and organizations needed to hire staff for doing them.
But OCR software has made the process much easier by automating the data extraction. Also, machines provide more accuracy than humans, so the chance of inaccurate data because of human error is significantly reduced.
Nevertheless, OCR services have eradicated the need for scanners and other hardware and given the facility to do those tasks using mobile OCR.
How does OCR Process Work?
All OCR solutions vary in how they work depending on how they are implemented and used, but the basic concept is the same. Similarly, every OCR provider has different services to offer but the OCR technology is the same.
Character recognition apps incorporate document processing mechanisms that allow it to read and extract information from documents. OCR technology separates the white spaces in the document from the characters, making it clear to read. Followed by this, it recognizes and separates different characters, and then grouped characters to detect words.
The different characters are assigned specific metadata and then matched by the software with previously saved fonts in the libraries. In addition, ICR (intelligent character recognition) is a new advancement to OCR technology that can even detect data from documents with cursive handwriting.
Using intelligent OCR, if there is a task to differentiate between characters such as “I” and “1”, it can determine which one it is by checking the characters before and after it and decide which one makes more sense in the given context.
A Mix of OCR and AI
OCR in itself is a powerful technology, but when incorporated in a system along with Artificial Intelligence, it’s a whole new story. OCR technology using AI and NLP (natural language processing) gives much more accuracy in reading information from documents.
OCR document scanners used by businesses provide efficiency and save the cost of hiring individuals to do the task of data entry. This is because AI can learn what to extract, store, and where to enter it.
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Pre-Processing
During the pre-processing stage, OCR technology works to adjust the brightness and contrast of the image in order to make it as clear as possible. This makes it easier to differentiate characters from one another. OCR App also clears out any distortion in the image.
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Data Extraction
Then the software differentiates characters using a technique that searches for text blocks and line or paragraph separations.
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Post-processing
The post-processing phase uses machine learning algorithms to detect different fonts, their sizes, and also templates used in the documents.
Types Of Documents Scanned Using OCR
OCR technology provides the functionality to extract data from three types of documents:
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Structured documents
Structured documents are documents with proper templates and proper divisions of specific data. These include government-issued identity documents, utility bills, credit cards, and driving licenses. These documents can easily be scanned using OCR because of their predefined templates.
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Semi-structured documents
Semi-structured documents are those documents that do not follow a set template but the information can be read easily. Invoices from supermarkets, and sales or purchase orders come under semi-structured documents.
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Unstructured documents
Unstructured documents differ from semi-structured documents in the level of standardization used to make them and the information they contain. These documents do not follow any predefined template, such as legal agreements which do have dates and written statements, but the structure is always different. Nevertheless, OCR technology can be used to extract data from unstructured documents successfully.
Concluding Thoughts
To sum it up, OCR technology has revolutionized data extraction from documents and hasn’t stopped since. The technology sees constant improvements and has proved to be very efficient in business use. The process of document validation has been automated with the help of OCR technology.
