Intelligent OCR vs Traditional OCR: What’s the Difference?

Data extraction and processing is a prerequisite for any business in this data-driven world. Various technologies may have to be used to extract usable and meaningful data from documents. However, choosing the right one from among those available for data extraction becomes business critical, especially if you are dealing with documents in different formats.

The two automated data extraction tools of relevance are intelligent OCR, otherwise called intelligent character recognition (ICR), and the traditional optical character recognition (OCR). Though the basic purpose of both is the same, understanding ICR vs OCR is important, and which one to choose depends on the requirements of your business.

In this post, we shall explore the difference between the two technologies, their benefits and some use cases.

OCR for Automated Data Extraction

Though OCR has evolved to be a legacy digital document processing technology, the term ‘traditional’ is used to refer to the basic technology that can extract data from text images and convert them into machine-readable and editable format.

This technology is employed to digitize a wide variety of materials, including scanned or photographed documents, printed books, newspapers, historical records, medical records and prescriptions, financial statements, PDFs and more.

The one thing to note here is that the ‘traditional’ OCR is best used to extract data from printed documents, where there is minimal to no handwritten notes, and when the document is well- structured.

Though the initial iteration of OCR was limited by being able to handle only one font at a time, and required images of individual characters for training, recent versions of it leverage the power of advanced AI to support different image file formats and fonts as inputs. This makes the OCR highly adaptable and accurate in application across various fields like banking, shipping, postal handling and more.

Best Use of OCR

The traditional form of OCR is best used with printed documents, such as for:

• Digitizing physical and printed documents.
• Extracting information from business cards and populating contact list.
• Processing business documents like invoices, receipts and cheques.
• Creating editable and searchable digital copies of legal documents, contracts and other PDFs.

How AI Enhances Modern OCR Capabilities

The integration of AI capabilities with the traditional OCR makes it an even smarter digital document processing technology. AI-enabled OCR uses machine learning (ML) algorithms, unlike traditional OCR software, which uses rule-based approach. This enables it to recognize characters, words, and even complex layouts with high accuracy.

The process of AI OCR typically includes:

• Image Preprocessing: Enhancing the quality of scanned images or photos.
• Character Recognition: Applying Neural Networks to recognize and interpret text.
• Postprocessing: Post-processing output through spell-checking and layout fix-up.

This innovative method allows AI OCR to handle different fonts, languages, and layouts.

What Is Intelligent Character Recognition and How Does It Work?

What differentiates intelligent OCR, or intelligent character recognition (ICR) from traditional OCR is that the former is capable of detecting and processing different handwritings and font types as well. Besides, ICR can also comprehend the contexts of a document, and recognize variations in handwriting.

This feature of ICR makes it an ideal intelligent data capture tool for most businesses requiring modern or multi-modal document management processing. ICR quickly captures data from scanned documents and digitizes it for reporting and business system integration. Moreover, ICR is equipped with AI, machine learning (ML) and natural language processing (NLP) algorithms, which makes it capable of self-learning, and it continuously updates its recognition databases. This makes it capable of achieving accuracy rates of over 97% for structured forms, while also being able to handle semi-structured or unstructured documents.

Though ICR is an automated data extraction tool adept at recognizing handwritten characters, it still has not evolved to interpret cursive handwritings with absolute accuracy. Nevertheless, it can still capably interpret handwritten characters, even though they are inherently more variable and unstructured than typed ones, provided they are not in very elaborate or intricate stylized cursive styles. This makes ICR ideal for text extraction from forms like insurance claims, surveys and more.

Furthermore, ICR technology is highly customizable for specific use cases and scalable to handle large volumes of data, making it ideal for various applications, from form processing to historical document digitization.
Best Use of ICR

ICR is best employed to process documents containing a combination of handwritten and typed characters like:

• Digitizing bank account opening, loan, medical claim or insurance application forms.
• Making digital copies of hand-filled surveys, customer feedback etc.
• Digitizing signatures, handwritten notes on documents, annotations and others.

OCR for Scanned Documents

The biggest advantage that OCR compared to ICR is its cost-effectiveness, especially for beginners of technology adoption or for small scale businesses. But you must also take into account that this affordability comes at the cost of lesser features compared to the modern and smarter ICR.

Also, another major drawback of OCR is that it cannot handle handwritten documents. But if your business doesn’t require you to extract data from such documents, the savings on not opting for the more expensive ICR can be significant.

ICR for Intelligent Data Capture

Though the challenge of recognizing and interpreting too intricate cursive handwritings has not been fully addressed yet, ICR can still extract data from a wide variety of documents with different handwritten styles and font types. Moreover, ICR boasts an accuracy rate of almost 97%.

With all the advantages over the traditional OCR, the biggest limitation of ICR is that it is much more expensive than the former.

Nevertheless, if your business has to handle handwritten and mixed content and formats of documents, this extra cost you pay for ICR can be recovered in the course of time. The smarter and more intelligent OCR would save you precious time, effort and also money spent on manual labor to review every document even after being processed by traditional OCR.

Also, ICR is not a plug-and-play tool as it optimizes its performance over a period of time as it trains itself with more types of documents (self-learning capability). However, this also makes it an excellent scalable solution as it can adapt to your evolving business needs.

How to Choose between OCR and ICR for Document Automation

You need to consider several factors while choosing between OCR and ICR. You must take into account your business requirements, budget, nature and complexity of the text you need to process etc.

Take a look at the table below for a quick understanding:

Wrapping Up

When it comes to traditional OCR vs intelligent OCR (ICR) for your business, you should weigh the pros and cons of both and choose the most suitable option.

If your business requires digitizing of large volumes of structured, semi-structured and unstructured documents that come in different fonts and handwritten formats, ICR would be your ideal choice, albeit its higher initial cost. And if you are exclusively dealing with large volumes of structured and machine-printed documents, the cost-effective traditional OCR may be the best fit.

If you are ready to transform the way your organization handles documents and want a professional opinion, feel free to consult with DeepKnit AI’s experts who can guide you in the right direction.