Utilizing Advanced Techniques for the Extraction of Handwritten Text in Challenging Scenarios and Diverse Languages
Аннотация
Handwritten text recognition is the computer's ability to capture and interpret handwritten input from various sources, including paper documents, touchscreen interfaces, photo scans, and more. It falls within the domain of pattern recognition, [16] specifically character recognition, aiming to transform spatially represented handwritten language into its symbolic representation. Each script consists of characters or letters with distinctive basic shapes. The primary objective of handwriting recognition is to accurately identify the input characters or images, which are subsequently processed by automated systems. This technology finds applications in recognizing various forms of handwritten content, encompassing digits, numerals, cursive text, symbols, and scripts in multiple languages, including English. The automated recognition of handwritten text holds significant utility across numerous applications where handling substantial volumes of handwritten data is crucial. These applications include address and postcode recognition on envelopes, amounts on bank checks, document analysis, and signature verification. Consequently, computers play a pivotal role in facilitating document processing, whereby handwritten text is scanned, converted into editable documents, and can be translated into local languages like Hindi for increased accessibility and usability.