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ICR: A New Dawn of Character Recognition Technology

Digital-only solutions are on the roll with technology picking up the pace every day. These methods are not only reliable and convenient for the business but for the customers as well for example information technology blogs as well since they provide them with a seamless experience each time. But old-school businesses running on traditional ways and means can no longer withstand the intensifying market competition. Due to the change in consumer behavior and interests, innovation has become inevitable. Manual data entry tasks are no more an option with advanced data extraction tools like Optical Character Recognition (OCR) replacing them.  

ICR, or Intelligent Character Recognition, is one step ahead of the conventional OCR technology that combines artificial intelligence models with character recognition to read a variety of handwritten, printed, and image texts. The extracted data is then converted into an electronic form.

ICR – Benefits and Shortcomings

Intelligent character recognition (ICR) technology is equipped with machine learning algorithms that allow it to read:

  • Fonts with different sizes, shapes, colors, and geometry
  • Handwritten fonts
  • Fonts in a different language
  • Digital and cursive signatures

ICR or AI-based OCR is based on artificial intelligence which means that it can learn information over time. The more data it analyzes and extracts, the better it gets at reading them properly. The learning rate is directly proportional to the variety and amount of documents processed. But since these AI models are in a constant phase of learning, it is likely that they will lack correctness if presented with a document they do not recognize.

Let’s understand this shortcoming with an example. Assume that the ICR is shown a document that it has never seen before. The technology will be unable to recognize what each field corresponds to in the document, and it wouldn’t be able to extract the information accurately. But the advantage of ICR here is that it will take into account the document and learn it for future data extraction, hence getting better each time. On the flip side, when it sees a U.S. driving license, which is quite a common document, the software instantly extracts relevant data from it.

Intelligent Word Recognition

Handwritten texts and signatures cannot be easily understood by a normal OCR engine. This means that this type of scenario has to be dealt with another type of technology.  IWR, also called Intelligent Word Recognition, reads handwritten text (alphabets, digits, special characters) by creating a mapping between pre-learned characters and the handwritten characters it is extracting. With ICR, handwritten or paper-based documents can be extracted in a matter of seconds. If there are some parts of the documents that the ICR does not recognize, it uses IWR to analyze the text and to assist it in character recognition.     

ICR Technology Walkthrough

Data Acquisition

The process starts with the end-user uploading a document (whether a digital one or paper-based with handwriting) to the system. Once a copy of the document is acquired at the ICR end, it is ready to extract relevant information for further processing.

Data Extraction

The data obtained for processing is put through a series of character recognition phases where it is applied pre-processing and the essential features are extracted. The first name, last name, DoB, and all other important details are extracted that are needed to create a digital receipt needed for identity verification.  If the document has handwritten text, intelligent word recognition methods are applied.

Data Management

The data extracted from the document is used for either creating another document with a digital format, verifying the identity of a user, or any other specific task. The user details are stored on an online database or cloud where they can be easily retrieved regardless of time or place.

To sum it all up, intelligent character recognition helps enterprises manage their users’ data by performing data extraction and management better.  It also helps automate the process of manually acquiring customer details for onboarding which allows businesses to cut on operational overhead. This ultimately improves customer satisfaction, retains more clientele, and creates a good brand image.

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Pete Campbell
Pete Campbell is a social media manager at Blastup.com who has worked as a database administrator in the IT industry and has immense knowledge about email marketing and Instagram promotion. He loves to travel, write and play baseball.

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