Optical Character Recognition (OCR) for PDFs.

What is OCR?

OCR stands for Optical Character Recognition. Optical character readers use automation to convert printed documents, such as receipts and invoices, into machine-readable PDFs that you can edit and share.

This eliminates the need for manual data entry, which can reduce human error and free up valuable time and resources. OCR means it’s also easier for businesses and individuals to store, organise, and retrieve important information.

Why is Optical Character Recognition (OCR) useful?

Despite living in a digital age, many businesses still use print media such as invoices, contracts, legal documents, and other forms of paper.

But physical documents often take up a lot of space and require time and effort to manage. That’s why paperless documents are seeing more use across businesses. Enter, Optical Character Recognition (OCR).

OCR can help in a number of ways:

Streamlines processes and increases efficiency.
OCR can save your business time and money by converting printed documents into digital files that you can easily analyse, search, and share. By integrating optical recognition into your business model, you can:

• Convert handwritten documents into editable PDFs files.
• Scan and convert documents, forms, and business cards into high quality PDFs.
• Locate important documents by searching for a specific word or phrase.
• Secure and streamline data all in one place.
• Mitigate human error and obtain the most accurate, up-to-date information.
• Convert handwritten documents to digital files that you can easily share with coworkers.
• Automate data entry. For example, easily extract data from customer invoices and upload them directly to your accounting systems.

Increases accessibility.
In addition to being able to scan and search text, OCR also provides greater accessibility for users who are blind or visually impaired. Users can scan a document and the Optical Character Recognition will read the text aloud.

The OCR text recognition technology also has a spell-checking function that corrects words that are spelled incorrectly, allowing for the most accurate information to be conveyed to users.

How does Optical Character Recognition (OCR) work?

OCR works in four simple steps:

1: Image acquisition.

During this stage, an optical recognition scanner reads a document and converts it to binary data. The OCR software then inspects the scanned image and identifies any light areas as the background and dark areas as text.

2: Pre-processing.

Next, the OCR technology cleans up the image and prepares it for reading by:

• Smoothing the edges of text images
• Removing any digital image spots
• Fixing any alignment issues
• Recognising script for multilingual OCR technology
• Cleaning up boxes and lines within the image.

3: Text recognition.

Once the text has been identified, the OCR technology uses feature extraction and pattern matching to process the text.

• Feature extraction. Breaks down glyphs into features like lines, line directions, and intersections. These features are then used to find the best available match among glyphs stored on the database.
• Pattern matching. A symbol or glyph from the original image is compared to a similar glyph that is already stored on the database. This method only works when the glyph stored on the database has a similar scale and font to the glyph added. Therefore, results tend to work best with images that contain fonts the system already recognises.

4: Post processing.

Once the content has been processed, the system converts the extracted text data to a machine-readable file, such as a PDF. Some OCR software can create annotated PDFs that include the before and after versions of a scanned document.

If the Optical Character Recognition doesn’t recognise the text, make sure that your scan is high quality, and not too dark. You’ll also want to check your document is straight and not skewed.

History of Optical Character Recognition (OCR).

Today, Optical Character Recognition plays an instrumental role in data extraction. Discover how it began and its evolution over the years.

• 1947. OCR applications could only handle one or two types of text. However, that year, Ray Kurzweil, an American computer scientist and author, founded Kurzweil Computer Products, Inc to develop the first OCR solution that could recognise any style of print. It was then that Kurzweil decided to question what his technology would be good for.
• After a brief encounter with a blind man on a plane flight, he discovered that the best use of his technology would be to aid individuals who are blind or visually impaired. So, he made a reading machine that could read text and translate text aloud.
• 1980. Kurzweil sold his company to Xerox, an American-based IT corporation. The company were keen to continue commercialising paper-to computer text transformation.
• 1990. With the widespread adaptation of computers and the internet in the early 1990s, OCR technology quickly started to gain popularity. OCR systems were used to digitalise everything from newspapers to books and magazines. The technology was also used to automate processes in the finance and health sector.
• 2000s. During the early 2000s, new algorithms were introduced to improve the hardware. These included OCR systems that were able to recognise a wider range of characters and languages. As a result, OCR began to be adopted by a variety of industries and sectors.
• Present day. Today, OCR technology is more advanced than ever before. The software provides users with nearly perfect conversions and workflows are automated through advanced methods of OCR. It’s also widely accessible and continues to increase efficiency for both personal and professional purposes.

Types of OCR technology.

OCR technology can be distinguished by their application and use.

• Simple Optical Character Recognition software. Works by storing different text and font image patterns as templates. The software uses pattern dash-matching algorithms to differentiate between text images and conducts a character-by-character analysis in its internal data base. The system can replicate the text word by word. However, not every font and handwriting style can be captured due to the unlimited number of styles, so the solution has its limitations.
• Intelligent Character Recognition (ICR) software. Modern OCR technologies can read text in the same way humans do. Using machine learning, this software is trained to act like humans. A machine learning system called a neural network examines text and repeatedly processes images. It works by searching for different image attributes, like curves and loops, to pull together a final result.
• Intelligent Word Recognition technologies. These technologies use the same rules as ICR but focus on whole word images rather than pre-modifying images into characters.
• Optical Mark recognition. This identifies watermarks, logos, and other text-based markings on a document.

Best OCR software.

Looking for effective OCR solutions to help manage your documents? Here are some of the best OCR software options for business and personal use:

1. Adobe Acrobat Pro.

Acrobat Pro provides all the essential OCR and PDF tools you need to manage and modify your documents.

With Acrobat Pro, you’ll have access to all the basic OCR features you need, plus:

• The ability to leave comments and feedback on PDFs.
• The option to compare two documents, which can be useful for comparing data, etc.

Acrobat OCR also works well with the Adobe Scan app — a free OCR software which enables you to scan documents and transform them into PDFs. Text is automatically recognised, and you can make any necessary adjustments as needed.

Start your free trial today.

2. OmniPage Ultimate.

OmiPage Ultimate is a powerful document conversion software. The software enables you to effectively digitalise documents that are editable and searchable. You can also send files to custom workflows, for seamless management.

3. Abbyy FineReader.

With Abbyy FineReader, you’ll have access to all the necessary tools you need to transform paper documents into digital files. The software can convert text to PDF, Microsoft Office, and many other formats. You can also compare documents, add annotations, comments, and more. Additionally, the software can convert many documents at a single time and can process up to 192 different languages.

4. Readiris.

Readiris can help you transform your documents into editable digital files in minutes. The software can support a variety of file formats and even lets you add signatures and passwords to your documents, along with comments, watermarks, and various other features.

This OCR software uses AI to extract data from documents with ease and efficiency. By not using a template format, the system doesn’t get rattled by dynamic content.

Using OCR in your day-to-day processes.

• There are various types of OCR software and features available to help streamline your day-to-day processes.
• Layout analysis software can interpret scanned documents and divide them into segments that are suitable for OCR.
• OCR engines can aid with character identification.
• Software development kits can integrate OCR abilities to other software. Examples include document imaging management systems, record management solutions, and form processing applications.
• Graphical user interface (GUI) on OCR engines.

OCR in business.
Document creation and collaboration are important parts of business operations. However, document management can be time-consuming, especially if you have large volumes of documents to handle.

OCR can help you streamline the process, saving you valuable time and resources. By eliminating the need for manual data entry, efforts can be focused on other tasks. Data can also be stored electronically, which saves on physical storage space and lowers printing costs.

Additionally, businesses can use OCR to view content online in an organised fashion. With OCR, everyone can access the same digital documentation, making it easier to receive copies of the most up to date information.

Important documents can also be protected with additional security measures, making it more difficult for unauthorised individuals to access sensitive information.

OCR technology in education.
OCR software can also be a great tool for students. Here are a few examples of how OCR can assist in education:

• Textbook conversion. Convert printed texts books into PDFs that can be read out loud.
• Make edits. Highlight important information and add annotations to scanned documents.
• Research and extract key information. Use the search feature to quickly locate important information, or key phrases.

OCR can also be ideal in assisting students with learning difficulties and visual impairment. For example, a paper homework sheet can be scanned and converted to a digital document. Students can then use screen readers and other assistive technologies to assist with reading the document.

OCR in healthcare.
In the healthcare industry, OCR can be used to handle important patient records like tests and hospital records. This can aid in streamlining workflow for healthcare professionals and decrease the amount of manual labour.

OCR can also help to ensure content is up to date, as it reduces the risk of manual error.

Additionally, OCR can assist in retrieving data from electronic health records. For example, with a quick OCR search, a doctor or nurse can quickly retrieve important information from a patient’s medical history report. OCR technology can also be used to scan prescriptions and other important documents. This reduces the chance of error, potentially improving patient safety.

The future of Optical Character Recognition.

OCR and machine learning have grown significantly over the past couple of decades and are only expected to advance over the coming years.

While OCR technology today is fairly accurate, algorithms are anticipated to become increasingly more precise. The next generation of OCR will now see much wider integration with artificial intelligence (AI) that is not limited to the character-matching software of previous iterations. OCR software will now also continue to think and learn more on its own, meaning it has the potential to become even more versatile.

A couple of key features to look out for include:

• Enhanced handwriting recognition. AI systems are expected to become more advanced at processing various handwritten text and styles.
• Real-time OCR. AI integration on mobile phones will allow real-time OCR capabilities.
• Advanced document analysis. AI OCR systems will allow for more advanced document analysis.
• Multi-modal analysis. AI will enable OCR systems to process and analyse various styles of information, such as images, audio, and even video.

Adobe Acrobat generative AI.
Adobe Acrobat generative AI Assistant is also available to assist you with document management. With the AI Assistant, you can ask questions about your documents, quickly gather insights, and use responses to inform your deliverables.

Discover more about the Adobe Acrobat Generative AI document & PDF tool.

Start adding OCR solutions to your workflow today.

By incorporating OCR into your workflow, you can improve time and efficiency. Adobe’s host of useful features also allow you to edit, customise, and manage your documents with ease.

• Edit PDFs
• Create PDFs
• Sign PDFs
• Organise PDFs
• Share & Protect PDFs