The optical recognition technology in assistive technology devices

The optical recognition technology in assistive technology devices

Mada Center

Research article Online Open access | Available online on: 25 November, 2020 | Last update: 27 October, 2021

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Volume 6

Issue 15

The optical recognition technology in assistive technology devicesOptical Character Recognition (OCR) plays a vital role in converting printed materials into digital text files. The use of OCR technology (OCR) has transformed productivity, increased engagement and motivation, and, most importantly, accelerated learning. The technology has also played a crucial role in improving the lifestyle of individuals requiring support and people with disabilities. OCR technology provides effective, efficient, and accurate document processing that converts paper or image original texts to editable formats and then, translates it into multiple languages.

Digital text is one of the numerous formats that make printed information accessible to a broader audience; other forms include audio, large print, and Braille. Digital text is incredibly accommodating for struggling readers, including those who experience learning differences such as dyslexia. The digital format makes it feasible for readers to see words on a screen and hear them read aloud at the same time, which promotes more ways to interlock with the information. It can also help children amplify independent reading skills.

Standalone OCR Devices:

The latest OCR technology comes integrated with various hardware like a smart reading pen, handheld magnifier devices, standalone CCTV devices, and braille devices. The basic functionality is the same but the accuracy varies with the device. The device camera scans the document and the OCR software then converts the images into identified characters and words and creates temporary files, including the text’s characters and page design. The identification process considers the logical form of the language. Solutions like Ebot Pro or Compact 10 HD portray all the key components of a flawless OCR device while also having other features. Such a system can recognize that a word spelled incorrectly at the beginning of a sentence is an error and can fix the error.

OCR systems use a dictionary and implement spell-checking techniques comparable to those found in many other word processors. The synthesizer in the OCR system then speaks the recognized text and the knowledge is stored in an electronic format. In certain OCRs, these temporary files can be translated to forms that can be retrieved by commonly used computer applications such as word processors, spreadsheets, and databases. A visually impaired or blind individual can access the scanned text by using adaptive technology devices that magnify the computer screen or provide text to speech or braille output.

Future – Machine Learning and Deep Learning:

The future of OCR technology is rebooting using artificial intelligence-based machine learning and deep learning technologies; these new technologies are not limited by the rules-based character matching of existing OCR software.

The latest updates in OCR technology will have a neural network that mirrors human brain function to confirm that the algorithms don’t have to depend on historical patterns to determine accuracy and the benefit will be that it can derive meaning from the recognized text and will help to automate manually intensive tasks such as document classification, data extraction, and storage. With this adaption, a disabled user will also benefit from enriched data, deeper analysis, and thoughtful recommendations.


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