Optical Character Recognition: Traditional vs AI-powered
OCR stands for Optical Character Recognition. It is a widespread technology to recognize text inside images, such as scanned documents and photos. OCR technology is used to convert virtually any kind of image containing written text (typed, handwritten, or printed) into machine-readable text data.
OCR Technology became popular in the early 1990s while attempting to digitize historic newspapers. Since then the technology has undergone several improvements. Nowadays solutions deliver near to perfect OCR accuracy.
Probably the most well-known use case for OCR is converting printed paper documents into machine-readable text documents. Once a scanned paper document goes through OCR processing, the text of the document can be edited with word processors like:
Microsoft Word
Google Docs
Before OCR technology was available, the only option to digitize printed paper documents was by manually re-typing the text. Not only was this massively time-consuming, but it also came with inaccuracy and typing errors.
OCR is often used as a “hidden” technology, powering many well-known systems and services in our daily life. Less known, but as important, use cases for OCR technology include data entry automation, indexing documents for search engines, automatic number plate recognition, as well as assisting blind and visually impaired persons.
OCR technology has proven immensely useful in digitizing historic newspapers and texts that have now been converted into fully searchable formats and has made accessing those earlier texts easier and faster. OCR tools are undergoing a quiet revolution as ambitious software providers combine them with AI. As a consequence, data capturing software is simultaneously capturing information and comprehending the content. In practice, this means that AI tools can check for mistakes independent of a human user providing streamlined fault management.
OCR Difficulties
Unfortunately, modern companies’ demand is rapidly outpacing this growth, and businesses are beginning to focus on artificial intelligence-driven alternatives to increase efficiency and become more important. Companies are turning to OCS as an AI-driven alternative because simply creating a document template is no longer sufficient.
OCR requires rules and templates to ensure that the technology captures the required data. Because of the lengthy and costly setup process, each change necessitates the creation of a new rule, and OCR necessitates the use of rule templates.
There is also the error stream that can occur if the document lacks flexibility in terms of variability. Because OCR technology cannot be fully automated, more and more rules must be shortened, and there can no longer be as many rules and templates as there were previously.
OCR with AI enhancements:
Because of the advancement of artificial intelligence, modern businesses have increased the level of automation that can be achieved, and OCR has been introduced as a means of automating manual business processes.
While AI-based OCR tools aren’t as flashy as other transformative technologies, they have the potential to be included on corporate balance sheets. AI and OCR have proven to be critical success factors for companies such as Google, Facebook, and Microsoft. Because the Ocr engine must be managed by a human user, using AI to troubleshoot saves employees a significant amount of time and effort.
OCR tools and artificial intelligence are critical components of the future for the sleeping giants in the field of digital transformation. OCR has the potential to assist countless organizations on their path to more efficient and productive workers.
A.I. enables the OCR system to consider all available resources and discover connections and correlations between data structures, resulting in an organic knowledge pool that adapts over time. This “knowledge pool” provides information on the status of data extraction, allowing for a more efficient and accurate extraction process.
If your company is having trouble utilizing the data it collects, the A.I.-powered OCR system is an excellent first step. With machine learning and OCR, you can concentrate on responding to the data collected rather than how it is collected. The software’s dependable data acquisition and transmission provide you with a comprehensive view of the company from top to bottom.
Traditional OCR vs AI
In this case, there is nothing wrong or right. It is determined by the type of documents to be processed, the available resources, and the system’s needs. OCR is useful in industries where large volumes of a few fixed types of documents must be processed. In other cases, this AI technology can load various types of invoices; the advantage is that you don’t have to manage a lot of things for different types of documents, but it can be difficult to implement at times.
The two technologies can be combined in various ways, such as by combining traditional OCR with artificial intelligence (AI). Both technologies can be used in a variety of ways, combining OCR and AI to process a wide range of documents, combining both benefits while maintaining their respective strengths and weaknesses, such as accuracy and speed.
The intriguing aspect of Gleematic is that everything can be done with the basic system they have developed, a robot that can do all of the human work and carry out the work process in a manner that is very much in line with current needs. With Gleematic, you can spend more time each day filling out recurring invoices for your business.
Wrapping Up
There is a significant difference between understanding a traditional OCR problem and viewing it as an AI-powered IDP problem that can significantly benefit business enhancement. OCR has the potential to be embraced as a disruptive new technology for automating traditional business processes. With the advent of artificial intelligence, modern businesses have raised their expectations of what automation is capable of.
The combination of optical character recognition technology and artificial intelligence is proving to be a winning strategy for both management and data capture. AI-powered OCR tools have proven to be a transformative technology, with a positive impact on businesses that consider adopting them. AI-powered OCR tools are sleeping giants in the larger context of digital transformations and technological advancements. As a result, technologies that reduce costs while maintaining high accuracy and efficiency are always preferred by business and financial infrastructures. Whether you are involved with Traditional OCR or AI-powered, TagX serves both types of automation with its OCR transcription services having an end-to-end data handling process offered by skilled professionals reducing the cost of data entry at various stages.