Machine Learning in the Field of Optical Character Recognition (OCR)
The paper starts with an introduction and brief background and history of Optical character recognition (OCR) systems, then the various techniques of OCR systems such as optical scanning, location segmentation, pre-processing, feature extraction and post-processing are presented.
Abstract
Optical character recognition (OCR) deals with the process of identification of alphabets and various scripts. Optical character recognition (OCR) is one of the trending topics of all time. Optical character recognition (OCR) is used for pattern detection and artificial intelligence. Machine learning is widely used in the field of OCR to provide good accuracy in the result. In Python, Pytesseract is an optical character recognition (OCR) tool for python. The paper starts with an introduction and brief background and history of Optical character recognition (OCR) systems. Then the various techniques of OCR systems such as optical scanning, location segmentation, pre-processing, feature extraction and post-processing. The different applications of OCR systems are highlighted next followed by the current uses of the OCR systems. The future of the Optical character recognition (OCR) systems with machine learning environment is presented.