Identifying the Roles of ICR (Intelligent Character Recognition) and AI (Artificial Intelligence) and Their Functions


AI (artificial intelligence) is a computer program designed to imitate human actions and the way humans think. AI has been widely used in various fields such as science, economics, engineering, and many others. Some notable examples of AI that we often encounter in our daily lives are Google Assistant, Chatbot, Netflix, and others. AI is equipped with neural networks, which are artificial neural networks like those of humans that are used to recognize the relationship between one information and another. This capability is applied in the ICR (Intelligent Character Recognition) system to process documents that are more complex than ordinary OCR. However, there are not many companies that take advantage of this technology because it is still a newcomer technology for these companies.

What is ICR?

ICR is a technology specifically designed to recognize various fonts and handwriting from an image and convert them into an easily readable text by a computer. ICR is a continuation of OCR technology that has a higher accuracy in digitizing notes, texts and written documents. The reason is that ICR uses an artificial intelligence system capable of recognizing text characters without using certain rules such as the ones seen in OCR. In the business world, ICR technology is commonly used to scan various physical document data into digital form and store it in a database, so that the data is more structured and able to occupy less storage space. This data will also be easier to access and process for business analysis purposes.

The difference between ICR and OCR can be seen from their work results and the technology used. In this regard, some businesses have their own reasons in their decision to keep using OCR or are switching to using ICR instead. Here are some of the differences between ICR and OCR.

  • ICR uses AI Neural Network, while the OCR system is template-based.
  • Template-based OCR uses a specific format to perform data entry, while cognitive data retrieval by ICR learns how to recognize different types of formats.
  • ICR is highly adaptive, flexible, and able to change the format of invoices or documents that can occur frequently. On the contrary, OCR is ideal for companies that have a fixed document structure.
  • ICR automatically flags anomalies and asks the user to check on them when needed, while OCR requires manual review from the user.
  • Templates must be manually created on OCR technology, while ICR does not require a template.
  • ICR can be used for identifying images, various handwritten forms, paper documents, and other documents. Meanwhile, the OCR API is not compatible with many types of data and is only specifically designed for digital text.
  • The ICR scanner stores the read information in the company’s database so that it is easy to find and retrieve. On the other hand, scanned results from OCR are more difficult to find because the document is only converted into a PDF file.

ICR service supported by artificial intelligence neural network is effective in extracting various fonts and handwriting from an image. The AI neural network is also able to learn the data on its own, which in turn can help the system work well. Any data processed by ICR will also improve the system’s learning process in scanning information from various structured and unstructured documents.

Many companies, namely in the fields of economics and finance, use ICR technology empowered by artificial intelligence to process their customer data, because it is considered faster and more efficient considering the large amount of data they receive every day. Furthermore, ICR can also reduce the potential for errors in recognizing various forms of text, especially handwritten notes.

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