What is Optical Character Recognition (OCR)?
Optical Character Recognition (OCR) is a technology that enables the conversion of different types of documents, such as scanned paper documents, PDFs, or images taken by a digital camera, into editable and searchable data. By utilizing image processing techniques and machine learning algorithms, OCR systems analyze the shapes and patterns of characters within the images and recognize them as text.
The process begins with preprocessing the image to improve its quality, which may include adjusting the brightness, contrast, noise removal, or skew correction. The next step involves segmenting the text into individual characters or words, which is essential for accurate recognition. After segmentation, machine learning models, such as neural networks, are employed to identify each character based on its unique features. This recognition process can be further enhanced with natural language processing (NLP) techniques to provide context and improve accuracy.
OCR plays a significant role in various applications, ranging from digitizing documents for archiving to automating data entry processes in businesses. It is widely used in industries such as healthcare, finance, and legal sectors, where converting physical documents into digital formats can increase efficiency and improve accessibility. As technology advances, OCR continues to evolve, integrating deep learning methods to achieve higher accuracy rates and better recognition capabilities.