Natural Scene Text Editing Based on AI
This addresses the need for error correction, text restoration, and image reusability in scene interpretation, but appears incremental as it builds on existing text editing methods.
The paper tackles the problem of editing text in natural scene images at the character level, enabling updates to uppercase letters, lowercase letters, and digits by learning and transferring font styles from source to target characters.
In a recorded situation, textual information is crucial for scene interpretation and decision making. The ability to edit text directly on images has a number of advantages, including error correction, text restoration, and image reusability. This research shows how to change image text at the letter and digits level. I devised a two-part letters-digits network (LDN) to encode and decode digital images, as well as learn and transfer the font style of the source characters to the target characters. This method allows you to update the uppercase letters, lowercase letters and digits in the picture.