Form dropout using distance transformation

Abstract

This paper presents a form dropout approach which employs a distance transform and its gradient flow. Form templates are pre-processed off-line to obtain their distance transforms and gradient flows. We demonstrate that various components in the form dropout algorithm can derive benefit from rich geometric information about the form template which are made explicit in the distance transform and its gradient flow. Experimental results are also presented.