How OCR + AI Works to Extract Text Accurately

Discussions around the benefits and advantages of AI-powered OCR are endless. Nevertheless, Optical character recognition (OCR), as a technology, has evolved much since its introduction in 1920 by physicist Emanuel Goldberg through his statistical machine.

In its most basic form, OCR is a technology that extracts letters and numbers from images, scanned documents and PDFs, and transforms them into machine-readable or editable texts. By doing so, OCR presents users with words and sentences from the original content source (scanned documents and images), which can be edited and reused without the need for manual, error-prone data entry.

Almost a century later, OCR is now a legacy technology, which is still widely used by enterprises and individual users. The advent of artificial intelligence (AI) has however enhanced the capabilities of the traditional OCR in many ways than one.

While the primary function of OCR systems is to combine hardware like optical scanners / specialized circuit boards with software to convert printed documents into machine-readable text, AI, with its intelligent character recognition (ICR) capabilities, provides the OCR software advanced features such as the ability to understand different languages or even handwritten documents.

Modern OCR systems or intelligent document processing (IDP) systems, along with machine translation support like DeepL, Google Translate, or custom NLP systems, can convert not only physical documents such as legal contracts, historical documents, resumes, invoices and more, into editable PDF files, but also translate them to the preferred languages. This allows users to easily search, edit and format the documents as required.

For example, we can use the Google Lens in our mobile phones to scan a restaurant menu in a different language, and the AI translates the text into a language of our preference in real time for easy readability and understanding.

How AI OCR Works Step by Step

Now that we’re aware of what a modern AI-enabled OCR system is capable of, let’s examine the different stages of it from scanning to the desired output.

The working of an AI-powered OCR can be divided into six different stages:

1. Image Acquisition: This is the first stage and involves capturing the image of the document using a scanner, camera or other specialized hardware.

2. Pre-processing: The second stage is pre-processing, which is done by the OCR software. At this stage, the quality of the captured image is enhanced by removing noise, de-skewing to correct alignment, thresholding, and extracting the image base line.

3. Character Segmentation: Individual characters from the captured image of the document are picked, separated, segmented, and then passed on to the recognition engine.

4. Feature Extraction: The Intelligent Character Recognition (ICR) feature of the OCR examines the segmented characters for different features like closed loops, lines, line directions, and line intersections. Characters like alphabets or numbers are recognized based on these features. Unlike traditional OCR systems that used pattern recognition, which was based on isolating character images called glyphs and comparing them with similarly stored glyphs in their databanks, modern AI-powered OCR systems apply rules regarding the features of a specific letter or number to recognize printed or handwritten texts in any fonts or types. It then maps the extracted features of the segmented characters to different categories and classes to ensure that characters are transformed into meaningful sentences.

5. Layout Recognition/Classification: In this step, the OCR system will analyze the structure of the document image, and divide the page into elements such as text blocks, tables, or images. The program then compares them with a set of pattern images, and after processing all likely matches, it’d return the recognized text.

6. Post-processing: The final step in the process is to improve the accuracy of the OCR results. The extracted data is never likely to be 100% accurate and hence the system would deploy a spell-checker or dictionary to improve the accuracy of the text. The final product would then be delivered as a digital file of your choice — an editable format like a Word document, or a PDF. Some systems would also give you the option to retain both the input image and the post-OCR versions for easier comparison and more complete document management. An AI OCR with machine translation support can go the extra mile by converting text images in other languages to a readable and editable language of your choice.

Benefits of AI-enabled OCR in Business

OCR offers many benefits to businesses, including:

• Improved Accuracy: Unlike traditional manual data entry methods, OCR captures data directly from the original source thereby eliminating the chances of typos, or misinformation due to factual errors in input.
• Cost Saving and Improved Efficiency: OCR cuts costs otherwise needed for employing more staff, and also on stationery like paper and other materials. Along with improved accuracy, it also improves efficiency with reduction in time taken for data processing.
• Enhanced Data Security: By digitizing documents and leveraging modern cloud storage technology, OCR ensures safer storage than in physical forms, which is prone to damage or loss due to various factors. It also enables easy but controlled access to documents and implement access restrictions.
• Improved Compliance: AI-powered OCR solutions provide advanced security and compliance features such as encryption, access controls and auditing capabilities to guarantee protection for sensitive information and ensure regulatory compliance.
• Scalability: One of the best features of an AI-enabled OCR system is that it can be easily integrated with existing systems and scaled depending on the changing business needs. It has proven to be a solution of benefits for industries like insurance, HR, and finance, which have to deal with vast volumes of documents on a day-to-day basis.

Conclusion

Transforming your business’ document processing requirements from the traditional OCR technology to AI-enabled OCR and intelligent document processing can help improve accuracy, efficiency, capabilities, scalability, and security. This can result in better cost savings, enhanced data quality, and a holistic improvement in your business outcomes.

DeepKnit AI’s world-leading intelligent document processing (IDP) solutions can help streamline your business workflows, irrespective of your organization’s type or size.

Contact us for a demo and discuss your unique business requirements.