One of the most common applications of computer vision is optical character recognition (OCR). OCR is the process of converting printed or handwritten text into a machine-readable format. This can be used to digitize documents, store them in a database, and search through them for specific information.
In this post, we are about to discuss the role of computer vision in OCR and how it can be used to improve the accuracy of this process.
So without further ado, let’s get into it.
What is computer vision and how does it work in OCR?
Computer vision is the process of using computers to interpret and analyze digital images. In order to do this, computer vision algorithms analyze the pixels in an image to look for patterns. These patterns can then be used to identify objects, faces, or even emotions.
OCR can be a difficult process, as it must be able to interpret a wide variety of fonts and handwriting styles. However, recent advances in computer vision have made OCR more accurate than ever before.
How accurate is computer vision technology compared to traditional OCR?
Traditional OCR accuracy rates are generally between 95-98%. This means that there is still a chance for errors, such as misinterpreting a letter or misreading a word. However, computer vision-based OCR can achieve accuracy rates of 99.5% or higher. This means that the chances of errors are much lower and that the OCR process is much more reliable.
Benefits of Computer vision in OCR
There are many benefits of using computer vision for OCR. Here are a few notable examples:
1. Increased accuracy
One of the main benefits of using computer vision for OCR is that it can significantly increase the accuracy of the results. This is because computer vision can be used to automatically identify and correct errors in images. This means that less time will be spent on manual data entry and more accurate results can be achieved.
2. Increased efficiency
Another benefit of using computer vision for OCR is that it can help to increase the efficiency of businesses and organizations. This is because the technology can automate many tedious and time-consuming tasks, such as data entry and document processing. This will free up employees to focus on more important tasks and will help businesses to improve their efficiency and productivity.
3. Improved user experience
Another benefit of using computer vision for OCR is that it can improve the user experience. This is because the technology can be used to search for information using images instead of text. This is a major shift in how people use technology, and it is opening up a whole new world of possibilities.
Examples of how computer vision is being used in OCR today
There are many examples of how computer vision is being used in OCR today. Here are a few notable examples:
Google’s Cloud Vision API
Google’s Cloud Vision API is a computer vision service that allows developers to analyze the contents of images. The API can be used to detect objects, faces, and even emotions. The Cloud Vision API can be used to build a wide variety of applications, such as image search engines and face recognition software.
Amazon’s Textract
Amazon’s Textract is a machine learning service that can be used to extract text and data from documents. The service uses optical character recognition (OCR) to identify text in images.
Adobe’s Sensei
Adobe’s Sensei is another machine learning platform that offers a variety of computer vision services. One of these services is optical character recognition (OCR) which can be used to build applications that can automatically read and analyze documents, such as invoices and tax returns.
Microsoft’s Azure Computer Vision
Microsoft’s Azure Computer Vision is a cloud-based computer vision service that offers a variety of features, such as optical character recognition (OCR), image classification, and object detection.
The future of computer vision in OCR and its potential impact on the industry
The future of computer vision in OCR looks very bright, as the technology is constantly improving and becoming more accurate. Additionally, the use of computer vision for OCR is becoming more widespread.
As more companies adopt the technology, the cost of using computer vision for OCR will continue to decrease. This will make it more accessible to a wider range of businesses and organizations.
The impact of computer vision on the OCR industry will be profound. Technology has the potential to revolutionize the way that businesses and organizations process information.
Computer vision has the potential to automate many tedious and time-consuming tasks, such as data entry and document processing. This will free up employees to focus on more important tasks and will help businesses to improve their efficiency and productivity.
Computer vision is also having a major impact on the way that people interact with technology. The use of computer vision for OCR is making it possible for people to search for information using images instead of text. This is a major shift in how people use technology and it is opening up a whole new world of possibilities.
Final Takeaways
As you can see, computer vision is playing a major role in the OCR industry. Technology is constantly improving and becoming more accessible. This is having a profound impact on the way that businesses and organizations process information. The future of computer vision in OCR looks very bright and the potential impact on the industry is huge. At Rewisdom.AI we can help you develop state of the art OCR solutions and products, we are just a click away.