To digitize documents, businesses are already familiar with OCR (Optical Character Recognition) applications. However, traditional OCR often has limitations because it relies strictly on predefined rules, while complex issues such as handwriting to font variations are difficult to detect.
Recognizing this, Artificial Intelligence (AI) and Machine Learning (ML) are integrated into OCR applications to increase their effectiveness. In this article, you will learn how AI plays a role in transforming the way OCR works.
Conventional OCR systems rely on pattern matching with training data that we have provided. If a document uses an uncommon font type, blurry photos, or is folded, the accuracy rate of traditional OCR will drop drastically. With the help of Machine Learning, OCR is now trained using vast amounts of data, allowing the application to:
One of the biggest challenges in document processing is handwriting; each person has unique writing characteristics, so every character will differ from person to person without a fixed training repository as a reference. With the help of AI based on Deep Learning and Neural Networks, AI is capable of:
The implementation of AI and Machine Learning has revolutionized how OCR works, shifting from relying solely on provided training data to creating more flexible and intelligent OCR applications that recognize handwriting, handle font variations, and even process damaged documents, photos, or complex backgrounds.
With more than 12 years of experience supporting digital transformation, KLIK Group is ready to help you identify and choose OCR solutions that are easy to integrate with your company’s workflow.
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