The future of OCR technology: Imitating human behaviour
Data capture ought to have been solved a long time ago! That’s what most people think, especially if they’ve never tried to work with OCR technology. It is genuinely surprising how hard this problem actually is, and how big an advantage a human mind has compared to a fixed algorithm.
All about OCR technology
In 1974, Ray Kurzweil invented a product that could detect text on printed documents through a visual or optical process. This product is called Optical Character Recognition (OCR).
What is the purpose of OCR? Kurzweil thought the invention would be an ideal product for the blind, and he further designed a read-aloud feature. But it was not until the 1990s that this product began to be used for digitizing print documents, namely old newspapers.
OCR technology has since become essential for businesses that convert physical documents with printed text and digital images or scanned documents into digitally readable text.
What does OCR mean? The acronym stands for Optical Character Recognition, which means a device or technology that can recognize text characters by a visual or optical process.
How does OCR work? For digital images or scans of documents, the OCR algorithm converts the file into a black-and-white photograph and scans the document, detecting areas that are light and dark.
The dark regions are detected as characters, and then the technology identifies the characters using pattern or feature recognition. Finally, the OCR tool produces a result of the recognized characters in a digital format so that they can be easily copied and pasted for analysis in the business system.
OCR tools are handy for company departments that process documents in PDF files. What is OCR in PDF? As with other digital or physical documents, PDFs “lock” text and may not be able to process or read the text digitally.
Businesses still need to extract that text for processing purposes, and thus the text can become digitally editable with OCR. PDF to Word document conversions are also easier to perform once OCR tools convert the text into a digital format.
With the popularity of PDF files for business documents, Adobe has created the Adobe Acrobat OCR tool to make PDF text extraction simple for single documents. For fast processing of multiple documents, however, Rossum’s IDP solution is more efficient. Rossum also supplies the ability to process documents and gain crucial insights intelligently.
The best OCR tools for a business will be able to detect text in any font or format. For the most reliability in detecting characters in a document, companies can implement an AI-powered OCR solution that will provide companies with the ability to automate data capture processes.
Optical Character Recognition online
With the introduction of the internet, OCR tools began to move online. In the 21st century, it is relatively easy to find useful Optical Character Recognition online websites and tools.
For example, the tech giant Google has several procedures and tools that can be classified as OCR. To extract text from image files, the “image to text converter Google Drive” process is among the most straightforward choices for OCR.
To use Google Drive as an OCR tool and convert PDF files to text, right-click the file you need to capture text from and select “Open with Google Docs.” The file, whether an image or a PDF document, will automatically be converted into a Google Document with digital text.
It’s best to be aware of several downsides to using Google Drive for OCR purposes. First of all, the file cannot be larger than 2 MB. Google also recommends traditional fonts such as Times New Roman and Arial for the best result, which means other fonts may not appear correctly in the detection process.
Additionally, tables, lists, and columns are more challenging to detect and, at best, will end up with incorrect formatting. At worst, they will not be detected at all.
This is why a more robust solution is needed for businesses such as Rossum. Rossum is a robust, AI-powered intelligent document solution that can accurately detect and capture text in any font and extract tables with proper formatting.
Optical Character Recognition scanner
Optical Character Recognition tools are commonly called scanners. There are two very different types of Optical Character Recognition scanner tools. One is physical, and the other is digital. In some instances, both types of scanners are used for OCR purposes.
For example, if a business needs an Optical Character Recognition PDF tool, the company could invest in both physical hardware and digital software. The physical scanner would be a device that can scan the printed document and convert it into a PDF file. Once converted, the digital PDF document would need to be scanned by the software scanner so that text detection could occur.
Instead of implementing both scanners in a business, however, it is possible to use an Optical Character Recognition machine learning software on its own. This kind of software can detect text in digital documents using machine learning for feature detection. If a business already has a traditional scanner device, they only need a software solution to detect the text from the scans.
Rossum is a machine learning solution that quickly and accurately scans documents for text and captures it with little human involvement. An intelligent digital platform like Rossum can make it easy for companies to save time and money on document processing.
Optical Character Recognition device
A physical Optical Character Recognition device can include anything from a heavy-duty multipage scanner to a handheld pen-like tool. The kind of device you choose will depend on the Optical Character Recognition requirements you need for the tool.
Individuals who are blind or need OCR technology for more simple tasks will find that an OCR pen device is more useful than software or a scanner. These pens can scan individual lines of text and either read them aloud or convert them into a digital file connected to a computer.
On the other hand, businesses would need a multipage scanner device because of the number of documents they need to scan.
Optical Character Recognition machine learning tools, however, can reduce the need for a physical device. Many of these tools are software instead of hardware. Optical Character Recognition software can take PDF and image files and convert them into digital text without the need to be connected to a physical OCR scanner.
Optical Character Recognition algorithms
For software and computer tools, it is necessary to have an Optical Character Recognition algorithm. The best algorithm for OCR will automate text extraction and be able to detect text from any file format accurately.
Companies interested in developing a program for OCR specifically for their organization would benefit from using a pre-designed Optical Character Recognition algorithm. PDF OCR algorithms can be found in online coding libraries, and open-source code can be edited as required by the organization.
Tesseract and Google’s Vision API are examples of OCR algorithms companies can use to develop their OCR tools.
The simplest way, however, to implement OCR tools in an organization is through Optical Character Recognition software. The software will already have an algorithm so that the company will not need to create or edit it. Additionally, if the software has Optical Character Recognition machine learning capabilities, it will be more flexible than a simple coded solution.
Optical Character Recognition examples
Optical Character Recognition, the technology that detects text in printed and scanned documents or images, can be best understood by examining how it works through an example. An Optical Character Recognition example can be either real-world or hypothetical.
In many cases, a real-world example will describe how a particular business used a specific OCR tool to the benefit of their company. It is easier to find real-world examples of businesses that used Optical Character Recognition software than to find a story of a company that used an online OCR image-to-text converter tool. For the latter, a hypothetical example might be easier to find.
Businesses could use a simple online OCR tool or a robust software solution to convert PDF to searchable text. Examples of both devices can help companies determine which one to use.
OCR online tools: measuring against the standard
While online Google tools for Optical Character Recognition are helpful in certain circumstances, such as Google Vision API and the tutorial from Google Drive, they are not capable of the same efficiency that a pre-designed, complex solution can provide.
Additionally, online OCR image-to-text tools lack the kind of integration that businesses require for their processes.
Instead of these tools, companies can look for OCR online solutions in software. Rossum is an AI-powered OCR solution that can be found online and quickly implemented seamlessly in a business’s technology ecosystem.
Unlike code-based solutions or online tools, Rossum can capture the data from multiple documents and formats and automatically enter it into the business system. For companies that currently use manual methods of data capture, Rossum’s intelligent document processing solution can lead to exceptional savings.
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Layout independent OCR technology
Parse business documents to data using a rich cloud API. Because when every layout looks different, a simple regex won’t cut it, but deep learning will.