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How intelligent character recognition works today and why it’s crucial

Admin by Admin
6 May 2023
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How intelligent character recognition works today and why it’s crucial
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As opportunities, competition, and the flow of supply and demand increases, the need to offer better services is also increasing for businesses. In a growing digital world, this increasing pressure on businesses demands them to utilize the best technological services.

Intelligent character recognition can help institutions streamline their processes particularly when it comes to document and paper processing. The technology is based on advanced, complex, and the latest research within the domain of computer sciences.  

Understanding Intelligent Character Recognition and How It Differs From OCR

Intelligent character recognition or ICR is based on OCR or optical character recognition principles. OCR has existed since the late 19th century and refers to the conversion of printed text into digital format. Computer-based systems primarily use intelligent character recognition to read handwritten text and convert it into a computer-readable format, which is an advancement over OCR technology. This makes ICR more extensive and detailed as compared to the conversion of typewritten content.

Understanding ICR Intelligent Character Recognition Technology

Handwritten text hosts a lot of variation as everybody writes in their own style. This requires ICR to be based on intelligent machine learning systems.

While machine learning is a primary technique that helps intelligent character recognition software online technology grow, several other computer techniques are also at play.

Image processing  

Processing handwritten text into digital format is only possible when the computer is first fed a picture of the handwritten text. This makes image processing a very crucial step of the intelligent character recognition process.   

  1. As part of the ICR process, the character recognition software starts with accepting an image to process. 
  2. The software then proceeds by first fixing the proportions and sizing of the image to properly align the text.
  3. It then processes editing techniques such as noise reduction and contrast building to make the text clear.
  4. Before the image can be processed further for intelligent character recognition, it is important that each character is clearly readable. For this, the software initiates feature extraction. This separates the text from the background of the image.

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Machine learning

Machine learning algorithms are very important for intelligent character recognition. Every person writes in their own style. Thus, while analyzing printed text requires only understanding the fonts, for ICR the computer must also be smart enough to recognize the differences in handwriting and perceive characters as the human brain does.

Machine learning algorithms are trained on large datasets to help the software with intelligent character recognition processing.

Natural language processing

Natural language processing or NLP is a technique that was born at the junction of linguistics, computer science, and AI. In this way, the computer or intelligent character recognition software understands the human style of linguistics.

Both spoken and written linguistics are involved in NLP. However, for intelligent character recognition only the processing of written language is required. 

Neural networks

Computer Neural networks are a form of AI algorithms. These work to replicate the human brain structure and connections. Neural networks for intelligent character recognition refer to the construction of interconnected nodes and pathways that allow the multidirectional flow of information. The best intelligent character recognition software utilize neural networks based on language processing systems within the human brain.

Optical character recognition

In its true essence and practical format, ICR works in conjunction with OCR technology. Most documents contain both printed and handwritten content, thus, requiring both technologies to work together. For example, in order to read a check at a bank, the software required will utilize OCR for the typewritten part of the check and ICR for the handwritten part of the check.  

The Importance Of Intelligent Character Recognition For Document Verification

Intelligent character recognition is revolutionizing the process of reading digital content in all domains from helping to read doctors’ prescriptions to students’ notes

ICR has applications in almost all industries. However, its prime use, which is applicable in almost all industries, is for processes pertaining to document verification and assessment.

Document verification through intelligent character recognition is relevant to almost all industries. For example:

  • Banks require analysis of documents such as identity cards, driving licenses, utility bills, tax forms, etc. This is important for customer onboarding as well as routine verification processes.
  • Today, many airports utilize intelligent character recognition for document verification by checking for passports, boarding passes, etc. at entry points.
  • Intelligent character recognition of content in insurance documents is essential for healthcare institutions for the immediate processing of patients.
  • Verification of identity documents such as state-issued photo IDs is important in almost all industries for security purposes

Conclusion

While optical character recognition has been in use in almost all industries for over a decade, intelligent character recognition is now gaining popularity among commercial institutions. Computer technologies are evolving at a fast rate, and this is reflected in the services that we have available today.

Such technologies help ease business and private processes and are slowly becoming necessary services. This is thanks to the efficiency, accuracy, and comfort that these bring.  

ICR has plenty of applications, today. However, it is expected to evolve even more in the future. This holds potential opportunities for massive applications, particularly for businesses with extensive ID verification requirements.

Also, Read: The Following: big data architect, “distributed data processing engineer”, and tech lead

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