Handwritten Text Recognition

Handwritten Text Recognition (HTR) is a system that interprets and digitises handwritten text from a variety of sources, including papers, notes, and historical records, using artificial intelligence and machine learning. HTR enables more effective searching, analysis, and storing of written information by transforming handwritten content into digital text. The technology usually consists of several steps, such as segmentation to separate individual words and characters and image preprocessing to improve the quality of scanned documents.Following segmentation, the system employs trained models, frequently derived from deep learning, to identify handwriting patterns and precisely match them to words or characters. Because HTR systems are flexible, they may learn to identify diverse handwriting styles and adjust to different alphabets and languages. These days, HTR is used in a variety of industries, including banking, education, healthcare, and archival work. It facilitates data digitisation, simplifies record-keeping, and makes it simpler to access important information found in handwritten documents.