What is Optical Character Recognition (OCR)?
Optical Character Recognition (OCR) is a technology that converts different types of documents, such as scanned paper documents, PDFs, or images captured by a digital camera, into editable and searchable data. It is a key component of the broader field of computer vision.
Working Principle
OCR software uses machine learning and image processing techniques to analyze the structure of the document and recognize the characters. The process typically involves three main steps:
- Pre-processing: This step enhances the quality of images by applying filters and correcting distortions.
- Character Recognition: The software identifies characters by comparing them against a set of predefined templates or through deep learning models that have been trained on a large dataset of characters.
- Post-processing: In this step, algorithms apply context and linguistic rules to improve accuracy and correct misrecognized characters.
Applications
OCR technology finds applications in various domains, including:
- Document digitization in libraries and archives.
- Data entry automation to reduce human error.
- Text extraction for accessibility services.
- License plate recognition in security systems.
Conclusion
OCR is an essential technology leveraging deep learning and computer vision to enhance how we access and utilize textual information in various formats.