Optical character recognition (OCR) is the use of technology to convert machine-printed or handwritten text into digital text. There are a variety of business applications for OCR, including invoices, business cards, receipts, bank checks, and more. The term intelligent character recognition (ICR or iOCR) is sometimes used for advanced OCR technologies specifically used for multiple fonts and styles of handwriting.
How does intelligent character recognition (ICR) work?
Most ICR systems use a machine learning technique known as a neural network which is able to "learn" and correct its performance over time. The network takes in massive quantities of handwritten training data with a variety of different styles and formats. It then compares each character with the training data to find the closest match and the most accurate transcription.
Thanks to artificial intelligence and machine learning technologies, ICR is able to recognize sloppy handwritten text that even humans have difficulties reading.
How is ICR used in the workplace?
Many organizations are eager to get started with robotic process automation (RPA), a revolutionary new business practice that uses robotic "agents" to automate a variety of processes.
For many companies, however, one major RPA roadblock is the need to scan, digitize, and transcribe large amounts of handwritten documents. Many forms filled out by consumers, such as registration forms and loan applications, are handwritten and in paper format.
Businesses devote large amounts of time and manual effort to enter this handwritten information into their software and systems. However, this is both slow and susceptible to errors.
The rise of OCR and ICR means that companies can vastly speed up and simplify the transcription of handwritten data. By using ICR to digitize handwritten forms and documents, you can automate the transcription process from end to end.
Tips for using ICR in your business
- Understand the limits of ICR technology. Although ICR is capable of processing a variety of documents, it needs to be trained to recognize them before you can incorporate ICR in your RPA projects.
- Find the right confidence threshold. ICR systems have a "confidence threshold" in the accuracy of their transcriptions, below which documents need to be manually inspected and approved. Experiment to find the threshold that you're most comfortable with.
- Use the appropriate training data. The more training data you have, the better. In addition, it's best to train your ICR system on real data that you've used and received from customers in the past.