ICR Technology was transformative to the modern world in a way the invention of Gutenberg’s press was to medieval Europe. It allowed corporations to process and store data in a streamlined fashion. The accuracy of the system is dependent on how a particular document is designed and written, still, it can go through a wide range of characters with ease. The new advances in the form of intelligent character recognition now allow the scanners to yield information into a searchable, editable format. This helped big data corporations to improve on their data handling and storage.
What is Intelligent Character Recognition Technology?
Intelligent Character Recognition (ICR) is a data extraction tool that can identify and capture text in its rudimentary form. It is a more refined, sophisticated iteration of Optical Character Recognition (OCR) that came before it and can read and store data from paper-based documents. Since the predecessor could only pick up printed data, ICR has taken things up a notch by discerning full characters from an image file, either printed or handwritten.
This is revolutionary in terms of cost and manual supervision of digitizing paper-based data. Since 65% of the global GDP will be digitized in a year, according to IMF’s surveys, ICR scanners will play a large role in abandoning primitive ways for the modern ones.
Mechanics of ICR Engine
The brain center of an ICR software is an artificial neural network (ANN). Contrary to legacy systems that need to be maintained and overhauled periodically, this network mimics the working of a human, thanks to AI and ML roots. So, the ICR algorithm continuously learns and improves its capabilities when it is exposed to new forms of data.
ICR Solutions commence their operations by trying to discern a generic path in a document, instead of focusing on characters. This allows them to come up with a premise or a context, thus ensuring more accuracy in the process.
In the coming section, we will discuss the confidence and accuracy of an ICR recognition tool.
Confidence and Accuracy of ICR Reader
A level of accuracy has always been attributed to automatic systems and processes to gauge their efficiency. This comes in handy to understand how much manual supervision an automatic system needs.
In ICR technology, precision and functionality are gauged on both accuracy and confidence, which are not synonymous in their meaning.
Accuracy defines the percentage of the text that is read correctly by the software. ICR technology does not calculate self-accuracy and it can only be determined after the automated process is finished and evaluated.
Confidence level shows how an ICR technology system is certain about a character or a field and then assigns a number to it. The range for the confidence index is 0 to 100 and is determined through the context of recognition. In case of indecision, the system will return the data with an indication to be manually reviewed. Also, the system can be furnished to assign confidence values to doubtful characters so that they can be rectified later on.
How to build on Accuracy and Confidence of ICR Technology?
The accuracy and confidence of ICR technology can be improved by limiting the context of readable information, especially in the case of handwriting. For instance, if you configure the system to read numbers only, it will read the hand-written information accurately.
Here are some other measures that can improve the working of ICR algorithms.
Point out to the users
To use bold characters and avoid cursive writing.
The form will be automatically processed.
Examples for effective character writing, such as how to write 1 or 7, or how to distinguish 8 from 3.
Use Cases of ICR Solutions
ICR technology has been adopted widely across governmental, intergovernmental, and private organizations for data extraction and processing. Since its development, the system has seen tremendous changes and helped multiple industries in their drive for digitization.
These are the industries that have benefited extensively from ICR technology:
1. Banking documentation was primarily paper-extensive. With ICR tools, banks have cut down drastically on their paper consumption and gone digital, resulting in efficient data keeping and processing.
2. E-commerce platforms use ICR scanners to verify electronic signatures of customers for the purpose of billing, authentication, and KYC compliance.
3. The automatic character recognition system has been widely accepted in the education sector in the last decade. Institutions use it regularly to grade papers and store them electronically for reference.
4. The logistics sector is also making great use of this technology to scan and store relevant data digitally, such as receipts, invoices, etc.
The Future of Digitization
Organizations are abandoning the old ways for a number of reasons, and digitization is the only way forward. A survey in 2018 by Forrester showed that 21% of North American and European corporations declared themselves to be completely digitized. ICR systems are powered by AI algorithms, which means they get even better at what they do when they are done with a new set of problems. With the advances in deep learning (DL) and predictive modeling, the system will be getting more accurate.