What Is The Difference Between OCR And IDP?

OCR (Optical Character Recognition) and IDP (Intelligent Document Processing) are two technologies that are increasingly being used in the world of document management. While the two technologies share some similarities, there are significant differences between them that can impact how they are used and the results they produce. 

In this article, we will explore the differences between OCR and IDP and how they can be used in document management.

What is OCR?

OCR is a technology that is used to convert scanned images of text into machine-readable text that can be edited, searched, and analyzed by a computer. It works by identifying characters in an image and translating them into text that can be read by a computer. OCR has been around for many years and is widely used in document management to automate the processing of documents. There are plenty of high-quality OCR providers, like SmartSoft.

OCR is typically used to convert scanned documents into searchable and editable text documents. OCR technology can be used for a variety of document types, including invoices, receipts, and contracts. OCR can also be used to recognize handwriting, although the accuracy of the recognition can vary depending on the quality of the handwriting and the OCR software being used.

OCR technology has some limitations. For example, OCR may struggle to recognize certain fonts, especially if they are unusual or if they are used in low-quality scans. OCR can also have difficulty recognizing text that is written in languages other than English.

What is IDP?

IDP, on the other hand, is a more advanced technology than OCR. IDP uses machine learning and other advanced techniques to process documents and extract data from them. IDP can be used to automate the processing of documents in a variety of ways, including data extraction, document classification, and data validation.

IDP can be used to automate the processing of a wide range of documents, including invoices, purchase orders, and insurance claims. IDP can also be used to extract data from documents that contain tables or other structured data. IDP can be used to validate data to ensure that it is accurate and complete, and it can also be used to classify documents based on their content.

IDP has several advantages over OCR. For example, IDP is more accurate than OCR because it uses machine learning and other advanced techniques to process documents. IDP can also be used to process documents that contain more complex data than OCR can handle, such as tables or other structured data.

The differences between OCR and IDP

OCR and IDP share some similarities, but there are significant differences between them. The main difference between the two is that OCR is a more basic technology that is used to convert scanned images of text into machine-readable text, while IDP is a more advanced technology that is used to automate the processing of documents.

OCR is typically used to convert scanned documents into searchable and editable text documents. OCR is useful when you need to be able to search through a large number of documents quickly or when you need to be able to edit the text in a document. OCR is also useful when you need to be able to extract certain types of data from a document, such as names, addresses, and dates.

IDP is a more advanced technology that is used to automate the processing of documents in a variety of ways. IDP is useful when you need to be able to extract data from a large number of documents quickly or when you need to be able to validate the accuracy of the data that is extracted. IDP is also useful when you need to be able to classify documents based on their content, such as invoices or purchase orders.

Another difference between OCR and IDP is that OCR is more limited in the types of documents it can process. OCR is typically used to process documents that contain text, while IDP can be used to process documents that contain more complex data, such as tables or other structured data. 

IDP is also better at recognizing handwriting and can be used to process documents in multiple languages, while OCR can struggle with recognizing certain fonts and non-English languages.

One of the biggest advantages of IDP over OCR is its ability to learn from previous processing experiences. IDP uses machine learning and other advanced techniques to improve its processing capabilities over time. As IDP processes more documents, it learns to recognize patterns in the data and becomes more accurate and efficient.

IDP can also be used to automate workflows, such as invoice processing or claims processing. With IDP, documents can be automatically routed to the appropriate department or individual based on their content, reducing manual processing time and errors.

Overall, while OCR and IDP share some similarities, they are fundamentally different technologies with different use cases. OCR is best suited for basic text recognition and data extraction, while IDP is more suitable for advanced document processing and automation.

Conclusion

OCR and IDP are both important technologies in the world of document management, but they have significant differences in terms of their capabilities and use cases. OCR is a basic technology that is useful for converting scanned images of text into machine-readable text, while IDP is a more advanced technology that can be used to automate the processing of documents in a variety of ways.

Regardless of which technology is chosen, the use of OCR and IDP can greatly improve the efficiency and accuracy of document processing and management, leading to significant benefits for businesses and organizations.