Optical Character Recognition (OCR), text from handwritten, typed, and digital images can be made readable for machines. In many businesses nowadays, OCR is quite helpful for converting a large number of printed or paper documents into digital text files. 

There are two parts to an OCR system, hardware, and software. A scanner that can scan paper documents or images into digital form can be the hardware part. In contrast, the algorithm itself comprises the software part. In terms of data entry, OCR has made a huge difference. OCR software allows fast conversion of scanned documents into searchable and readable text files. 

What is Optical Character Recognition?

Transforming an image of text into machine-readable text involves the technique of optical character recognition (OCR). Your computer will save the scan as an image file, for instance, if you scan a form or a receipt. The words in the image file cannot be edited, searched for, or counted using a text editor. A text document can be created from an image, however, and the contents can be saved as text.

Different Types of Optical Character Recognition

Experts in data sciences, classify OCR into different types based on their working process and use. Here are some examples mentioned below:

Normal OCR software 

This OCR technology works by saving a number of different text images, fonts, and styles as templates. A pattern-matching algorithm examines each character of a text image and compares it with its internal database. If the patterns match, OCR is able to recognize the text image. It is referred to be optical word recognition if the system matches the whole text word by word. Because there are so many different font and handwriting variations, it is impossible to capture and save every single one in the database, which places restrictions on this solution. 

Intelligent Character Recognition (ICR) software

Using Intelligent Character Recognition (ICR), modern OCR systems read text similarly to humans. With enhanced methods, they use artificial intelligence and machine learning to train machines to work like humans. The text is analyzed on a number of levels by a machine learning system known as a neural network, which repeatedly processes the image. The ultimate result is obtained by combining the findings from each of these many layers of analysis. It searches for various image features such as curves, lines, intersections, and loops. 

Intelligent Word Recognition (IWR)

Similar to ICR, intelligent word recognition systems process entire word pictures rather than first converting them into characters.

Optical Mark Recognition (OMR)

This type of OCR identifies the text symbols in the documents, logos, and watermarks. 

Optical Character Recognition Benefits for Data Entry

There are a number of optical character recognition benefits, but its biggest benefit to businesses is that it makes their job more productive and efficient. Particularly in office environments where there is a lot of document input and scanning, its ability to quickly search through large content is very useful. Here are some major optical character recognition benefits:

High Efficiency

OCR programs help companies to achieve higher efficiency by facilitating quicker data processing when needed. Employees no longer have to spend time and energy extracting relevant data, allowing them to concentrate on their core tasks. Employees do not have to visit central record rooms again and again. 

Cost Efficient

One of the most significant optical character recognition benefits of data input technologies is that they enable organizations to avoid hiring specialists to perform data extraction. Additionally, this software aids in reducing several other expenses like copying, printing, shipping, etc. This is because OCR eliminates the cost of lost documents. 

High Accuracy

Inaccuracy is one of the main issues for data entry. Data entry with automated tools, such as OCR, is more efficient because errors and inaccuracies are reduced. OCR for business in data entry can also be effective in preventing problems such as data loss. Because of no human involvement, there are zero chances of entering wrong information. 

High Security 

Data security is one of the most essential tasks for any organization. Paper-based documents are most likely to destruction. A natural element such as moisture, pests, or fire can be used to destroy papers, causing them to be lost, stolen, or destroyed. Unlike scanned data, digital data is analyzed, stored, and preserved digitally. Additionally, to prevent mishandling of digital documents, access to these documents can be minimized.

Final Thoughts

Using OCR solutions makes it simple for any organization to maintain documents internally, providing a start to automate workflow, and reducing the need for paper-based processes. High-level OCR could be useful for medium- and large-sized businesses to generate revenue utilizing specially crafted algorithms. OCR in business like healthcare, banking, and tourism, can be more beneficial.