Recognition-Independent Handwritten Text Alignment Using Lightweight Recurrent Neural Network
Karina Korovai, Dmytro Zhelezniakov, Olga Radyvonenko, Oleg Yakovchuk, Ivan Deriuga, Nataliya Sakhnenko · 2023
Legibility refers to the ease with which handwritten content can be read and understood accurately. However, existing approaches to handwriting beautification either rely on the result of handwriting recognition and accumulate errors from the recognition system or do not address the alignment problem and are difficult to generalize to other languages. This paper presents a novel approach to improve handwriting legibility by straightening the written content. It utilizes a recurrent neural network that operates without the need for recognition, supports connected writing, and accommodates various writing styles. The results obtained with this method demonstrate significant improvements in handwriting alignment. Moreover, a single neural network model can effectively cater to multiple languages within the same writing system.