Transforming physical documents into digital files is a step in the right direction for improving office processes, saving business costs and helping achieve sustainability goals. But simply having digital copies isn’t enough — you also need to be able to edit these documents in their digital format.
Optical character recognition enables you to do this. In this blog, we explain what optical character recognition is, how it works, why it’s essential for your business and predict what will happen as technology advances.
- What is optical character recognition?
- How does optical character recognition work?
- Why is optical character recognition so important for document management systems?
- Who can benefit from optical character recognition?
- The future of optical character recognition
What is optical character recognition?
Optical character recognition, or OCR, is a technology designed to recognise and extract text from images, such as scanned documents, photographs or other visual representations of text.
It’s one of the most well-known technologies businesses use when transferring their physical documents to electronic files during the mitigation phase.
How does optical character recognition work?
The primary goal of OCR is to convert non-editable text, which is embedded in images, into machine-readable and editable text.
Here's a quick step-by-step explanation of how OCR technology works.
Image acquisition
- The process begins with acquiring an image containing text
- This image can be obtained through scanning physical documents, capturing photographs or any other means of obtaining visual representations of text
Preprocessing
- The acquired image undergoes preprocessing to enhance the quality and clarity of the text
- This may involve tasks like image cropping, deskewing (straightening tilted text) and noise reduction to ensure better recognition accuracy
Text localisation
- OCR software then analyses the preprocessed image to identify the regions where text is present
- This step is crucial for isolating and extracting the text from the rest of the image content
Character segmentation
- Once the text regions are identified, the OCR system segments individual characters or words
- This involves breaking down the text into smaller units to facilitate accurate recognition of each character
Feature extraction
- Extracting distinctive features of each segmented character is the next step
- Features may include aspects like shape, size and spatial relationships between different parts of the character. These features help to distinguish one character from another
Character recognition
- The extracted features are used to compare and match the segmented characters against a pre-trained database of known characters
- OCR algorithms use pattern recognition techniques, which could include machine learning models or neural networks, to identify the characters
Text reconstruction
- After individual characters are recognised, they’re reconstructed into words and sentences
- This step involves understanding the context and arrangement of characters to form coherent text
Output generation
- The final output of the OCR process is machine-readable and editable text
- The text can be used for various purposes, such as indexing, searching or editing within digital documents
OCR technology has applications in document digitisation, data entry automation, text extraction from images for translation services and making printed material accessible for people with visual impairments.
It plays a crucial role in transforming non-textual information into a format that can be easily processed by computers and integrated into various applications — a necessity as we move further into the digital era and shift from physical documents in filing cabinets.
Why is optical character recognition important for document management systems?
There has been a huge shift in how businesses perform and hold data over the last decade.
Rather than relying on physical documents, which are at risk of damage, disappearing or security breaches, documents stored digitally in a document management system and on the cloud eradicate each of these risks.
We’ve broken down why this technology is crucial for document management systems.
Enhanced searchability
OCR enables businesses to make their documents searchable by converting images of text into machine-readable text and storing them within a DMS. This significantly improves the ability to search for specific information within documents, making data retrieval faster and more efficient.
Improved document accessibility
By converting printed or handwritten text into machine-readable formats, OCR enhances document accessibility. It’s particularly valuable for employees with visual impairments, as well as for creating an inclusive workplace where many have adopted remote working.
Efficiency in data entry
OCR automates text extraction from documents, reducing the need for manual data entry.
This not only saves time but also minimises the risk of human errors associated with manual input. Research from 2022 shows that error rates for manual entry sit at around 1%, and while this may seem like a small percentage, one incorrect figure within those entries could lead to severe consequences such as reputational damage, legal action and hefty fines.
Using OCR to transfer documents to a document management system (DMS) means businesses can streamline data entry processes and allocate resources more efficiently.
Streamlined workflows
Businesses often deal with large volumes of documents that need to be processed and managed.
OCR contributes to streamlined workflows by automating tasks such as document categorisation, content extraction and indexing, leading to improved overall efficiency and productivity.
Data accuracy and integrity
OCR technology is designed to achieve high accuracy in character recognition, which contributes to improved data accuracy and integrity, especially in industries where precision is critical, such as finance, legal and healthcare.
Cost savings
Automated text extraction through OCR reduces the reliance on manual labour for data entry tasks, resulting in cost savings for businesses by minimising the need for additional personnel and reducing the time required for document-related processes.
Compliance and audit trails
OCR aids in maintaining compliance with regulatory requirements by ensuring accurate and searchable records.
Additionally, creating text-based indexes also contributes to establishing robust audit trails, which is crucial for industries that require detailed documentation for compliance purposes.
Integration with business systems
OCR technology can be integrated into existing business systems and applications, enhancing their capabilities without requiring a complete overhaul. The flexibility on offer allows businesses to leverage OCR for specific needs within their current infrastructure.
Improved customer experience
Businesses can use OCR to enhance customer experience by efficiently processing and retrieving information from documents. This is particularly relevant in customer service, where quick access to accurate information can improve customer satisfaction.
Who can benefit from optical character recognition?
OCR technology benefits a wide range of individuals, businesses and industries. Any industry or business dealing with paper-based or image-based documents can benefit from OCR by improving document management, searchability and overall workflow efficiency.
Here's an overview of who can benefit from OCR and how it’s utilised in modern businesses, along with typical use cases and industries that can leverage OCR.
Individuals
Individuals can benefit from OCR in personal document management. It allows them to digitise and organise their paper-based documents, making searching for specific information easier, creating digital archives and sharing documents electronically.
Small and medium-sized businesses
SMBs can use OCR to streamline document-related processes, reduce manual data entry efforts and enhance the efficiency of their workflows. OCR is particularly beneficial for businesses dealing with a significant volume of paperwork.
Enterprises
Large enterprises often deal with vast amounts of data and documents. OCR helps them digitise and manage these documents more efficiently, improving data accuracy, searchability and overall document accessibility.
Financial institutions
Banks, financial services and accounting firms benefit from OCR by automating the processing of financial documents such as invoices, receipts and statements. This leads to improved accuracy in financial data and faster transaction processing.
Healthcare industry
Healthcare organisations utilise OCR for digitising patient records, medical forms and prescription documents. OCR enhances data accuracy, facilitates quick access to patient information and supports compliance with electronic health record (EHR) standards.
Legal services
Law firms and legal departments often handle large volumes of documents, including contracts, court filings and legal correspondence. OCR helps in converting and managing these documents digitally, making information retrieval more efficient.
Retail and e-commerce
Retailers and e-commerce businesses use OCR for processing invoices, purchase orders and shipping documents. This streamlines inventory management, order processing and other related tasks.
Logistics and supply chain
Logistics and supply chain management companies benefit from OCR in handling shipping documents, delivery notes and invoices. This improves the accuracy and speed of processing orders and managing inventory.
HR
OCR is employed in HR departments to digitise and manage employee records, resumes and other HR-related documents. This enhances the efficiency of recruitment processes and employee onboarding.
Typical use cases for OCR services in modern businesses include:
- Incoming invoices: OCR automates the extraction of information from incoming invoices, facilitating faster processing and reducing errors in financial transactions
- Payment advice: OCR helps extract relevant details from payment advice documents, improving payment processing accuracy
- Delivery bills and receipts: OCR assists in digitising and organising delivery bills and receipts, making tracking shipments and managing inventory easier
The future of optical character recognition
In 2023, the global optical character recognition market size was valued at $12.56 billion, with growth expectations of 14.8% to 2030.
The OCR market isn’t going anywhere. We can only predict what it will develop over the upcoming years, especially as we adopt machine learning, automation and artificial intelligence.