Document management across organizations has changed, and businesses are quickly realizing the undeniable importance of OCR capture and the role it can play in boosting document workflow across the company.
Businesses are realizing that reading unorganized documents can become tiresome, and sorting through heaps of text manually is exhausting, error-prone work that frequently results in critical information being overlooked.
There’s a new player in the game, and it will change the landscape of boosting document workflow forever. It’s called optical character recognition (OCR).
In this comprehensive OCR guide, we will tell you what OCR is and how it can boost your document management efficiency. Let’s begin!
What Is Optical Character Recognition (OCR)?
Optical character recognition (OCR) is a game-changing technology that takes document management efficiency to new heights. It transforms written materials into dynamic, searchable, and easily readable resources by seamlessly converting printed or handwritten text into digital data.
With OCR capture, businesses can digitize the process of reading and converting written or printed text into machine code, which the computer can modify. It is a subset of image recognition technology and is used as an efficient data entry tool, too, such as for accounting records, receipts, sales invoices, and even passports.
How Does OCR Work?
There are three steps that an OCR software takes to process an image or document:
Step 1: Image Pre-Processing
OCR software typically pre-processes images to increase the chance of accurate recognition. The goal of image pre-processing is to improve the original image data.
In this way, undesirable visual distortions present on the document being scanned become less prominent while the actual characteristics are highlighted.
Step 2: Character Recognition
The OCR needs to recognize the characters it wants to extract so it can recognize characters. When the input data is too large, the software only chooses a subset of characteristics is chosen.
The traits chosen are assumed to be the most important, while those deemed irrelevant are ignored. The performance is improved using a smaller data set rather than the initial large one.
Step 3: OCR Post-Processing
The OCR capture software conducts an additional error correction in the post-processing phase to produce highly accurate results.
A list of terms can be used to limit output and improve precision. For example, the algorithm can rely on a list of terms appearing on the scanned page.
Applications of OCR Capture in Document Management
Document management systems can use OCR for various purposes, such as extracting data from different documents, making it easier for businesses to digitize information in structured formats.
OCR can help any organization capture data efficiently and enhance its document workflow. Paper and electronic documents can be recorded into a single central repository and indexed to make them easier to find.
You’ll spend less time searching for documents and more time providing excellent client service or transferring information. You can also use the time saved to concentrate on more critical business tasks.
OCR provides benefits to industries ranging from banking and finance to healthcare, legal, and accounting. Here are some examples of common OCR applications in various industries:
- In the healthcare industry, optical character recognition can capture patient records such as treatment, lab reports, and doctor’s notes.
- Local governments can turn decades of public records into searchable digital files.
- Law firms can digitize years of records and cases.
- Universities can process HR paperwork for students and employees more quickly.
- Organizations can ensure on-time payment by intelligently capturing data from bills, invoices, and receipts.
OCR Capture Benefits for Your Business
Optical character recognition (OCR) capture has several benefits, whether in a corporate setting, learning environment, or personal use. The most important ones are as follows:
1. Boosts Efficiency
OCR technology boosts document workflow by streamlining the process of delivering data. Digitizing data reduces the need for manual labor to organize paper documents and saves time and energy, which can be invested elsewhere.
Digital data is more reliable than written documents and can be sorted and retrieved as needed.
2. Ensures Data Accuracy
Optical character recognition software can extract data with more than 99% accuracy through automated data entry. This technology also tackles issues related to incorrect or outdated data and loss of data.
Entering data with efficient OCR capture benefits organizations because it can help you efficiently capture data while also boosting document workflow.
3. Increases Compatibility
OCR capture helps with extracting automated data from written or printed documents. One of the great things about OCR is its versatility and the wide range of supported formats: DOC, DOCX, XLS, XLSX, TXT, searchable, JPEG, PNG, and TIFF.
Top OCR solutions
1. Filestack OCR API
On the API front, the Filestack OCR API is designed to integrate OCR capabilities seamlessly into applications. It supports a range of file types and is developer-friendly, enabling easy implementation of OCR functionality. It’s often utilized in scenarios requiring real-time text extraction, such as document management systems and content processing pipelines.
2. Tesseract OCR
Among the various OCR solutions available, Tesseract OCR is an open-source option widely recognized for its accuracy. Developed by Google, it supports multiple languages and can be customized for specific use cases.
3. ABBYY FineReader
ABBYY FineReader is a commercial OCR software known for its advanced capabilities, offering accurate text recognition, layout retention, and support for a variety of file formats. It is often used in document digitization and data extraction applications.
4. Adobe Acrobat
Another notable OCR solution is Adobe Acrobat, which provides OCR functionality as part of its broader document management features. It allows users to convert scanned documents into searchable and editable files.
All these OCR solutions differ in terms of licensing models, ease of use, and specific features; they collectively contribute to the broader goal of automating text extraction from diverse sources.
Best Practices for OCR Efficiency Across the Organization
Let’s look at some best practices for OCR efficiency across the organization:
- Proper Training of Users
Efficient OCR implementation can be done across your organization if the users are empowered and adequately trained. This reduces errors and delays in digitization, and users can quickly clarify concerns.
- Change Settings to Support Multiple Languages
You can also change the settings of your OCR software to support more than one language so it can scan text over a wide range of content.
- Keep Up with Our Latest Updates
To make the best use of Filestack’s efficient data capture and OCR document optimization, please also keep up to date with the latest Filestack features and updates for the best possible performance.
- Pre-Process Images to Ensure Document Quality Is Not Compromised
You can also reduce potential obstacles in the process of OCR capture by using pre-processing techniques to manage document quality variations such as distorted images or low resolution.
Conclusion
The future of document digitization and management is here. A reliable OCR solution can help you manage all your documents efficiently, accurately, and productively. Explore all your options to streamline your organization’s document management efficiency.
FAQs
How does OCR capture enhance document management efficiency?
Answer: OCR (Optical Character Recognition) capture transforms printed or handwritten text into machine-encoded text. In the context of document management, it expedites the digitization process, making documents searchable and editable, ultimately streamlining efficiency.
What are the key benefits of incorporating OCR capture in document management workflows?
Answer: OCR capture brings multiple advantages, including improved searchability, reduced manual data entry, and enhanced accuracy. It empowers organizations to efficiently manage large volumes of documents, leading to time savings and increased overall productivity.
How can businesses implement OCR capture effectively for optimal document management outcomes?
Answer: Implementing OCR capture for document management involves selecting the right tools, integrating them into existing workflows, and ensuring proper training for users. This comprehensive guide will delve into the steps, and best practices to help businesses seamlessly incorporate OCR capture into their document management strategies.