Intelligent Character Recognition (ICR), also referred to as Intelligent OCR, is a new tech that extracts written characters from pictures.
It is a more enhanced version of OCR technology in which Machine Learning techniques and AI smartly analyze the data in the form of physical documents by recognizing different handwritten styles and formatting.
ICR technology is used to detect and retrieve data from physical documents, which are then preserved in a database in digital form. The information is incorporated into workflow automation and used for analytical reporting. Companies use ICR techniques to organize disorganized data and generate reports that provide insightful information.
ICR enables customers to efficiently read handwritten paper documents and transform them into digital data. ICR systems collaborate with OCR to digitize information gathered from forms, removing the need for writing data manually. It has a high degree of precision and is a dependable way to save time when handling a wide range of documents
How is ICR Different From OCR
Companies obtain a huge amount of documents in the form of JPEGs, spreadsheets, PDFs, and other kinds of data. The wide range of file types makes processing this information complicated, and the OCR system is being utilized for automated processes. Cognitive data capture service enables the addition of human interpretation to data and the organization of unorganized fields.
The discussion over OCR versus cognitive data capture strategies is far from over, and there are multiple explanations for why some companies prefer ICR over OCR and the opposite.
The effective strategy is to use both, and the following are the major differences between them:
- Unlike ICR, the OCR method is pattern-based and does not use AI’s neural network model to extract data.
- Template-based For data input, OCR employs a particular layout, whereas cognitive data capture services begin to spot a variety of formats.
- OCR is suitable for businesses that have a set structure for their documents. ICR is adaptable and has been trained to handle regular invoice changes.
- OCR software requires task administration costs, whereas ICR software is completely automated.
- For OCR-based methods, manual data entry and review are required. ICR only indicates errors and requests that users check them when necessary.
- OCR requires the creation of templates by hand. Templates are not required for ICR.
- OCR APIs really aren’t developed to function with customized data and are only meant to operate with digital text. ICR uses handwritten forms, paper documents, images, and so on.
- Because OCR only converts files into PDFs just once, that’s why they are not easily discoverable in corporate databases. ICR scanners save read information, making data retrieval easier.
How ICR Operates
Robotic process automation is a process that automates the configuration of the ICR system and the execution of tasks without errors. Machine learning, voice and pattern recognition, and artificial intelligence (AI) are features used in conjunction with robotic automated processes and ICR to expand the range of modern ERP suites. The data produced is accurate, and ICR enables humans to glean information from advanced analytics, assisting them in making critical business decisions.
That is how ICR works during document extraction:
- First, the files are uploaded to the document scanner
- APIs that are pre-trained check all the data and scan the picture. The system interprets any handwritten characters and formats automatically, using a pre-existing repository as a reference
- For identification purposes, the software may request the customer to provide handwritten signatures
- Information is retrieved from files and organized automatically utilizing key-value pairs
- After reviewing and evaluating for spelling mistakes, the ICR operating system flags errors (if any are discovered) and sends documents to customers for overview.
- Otherwise, the files are analyzed and the information from the segments is automatically added into accounts payable frameworks for records management.
When the consumer wishes to submit more files in the future, the APIs will immediately develop new designs for analyzing and understanding information as new document forms are presented. When the same types of files are uploaded, it will scan and decrypt data using older models
ICR is a self-learning process, which means that it understands, evolves, and transmits data to databases better each time it is exposed to new handwriting patterns and formats.
Businesses can benefit from it in these ways:
- ICR is a comprehensive tool for preserving data archives, it can also be used for record-keeping
- Companies are implementing ICR with transcription services and trying to integrate with a variety of data files
- ICR solutions provide strong data verification while removing the need for entering data manually. As a result of this, employees are able to work more effectively and efficiently
- When uploading documents with ICR technology strategies, cloud storage seems to be more protected, and organizations can reliably safeguard information from unauthorized access
ICR solutions are fueled by intelligent neural networks that are continuously improving and are adaptable to new handwriting formats. We can say that as technology advances, so does the accuracy and reliability of intelligent character recognition. Users benefit from having more information to present to ICR models because the operating system can update and perform effectively.