A novel segmentation dataset for signatures on bank checks

TL;DR

This paper introduces a high-resolution dataset of bank checks with complex backgrounds, containing detailed segmentation masks for signatures, aimed at improving signature extraction methods.

Contribution

It provides a new, comprehensive dataset with pixel-level and patch-level signature masks on bank checks, facilitating advanced signature segmentation research.

Findings

Dataset includes diverse sources and complex backgrounds.

Manually generated pixel-level masks for accurate training.

Automated script produces consistent patch-level masks.

Abstract

The dataset presented provides high-resolution images of real, filled out bank checks containing various complex backgrounds, and handwritten text and signatures in the respective fields, along with both pixel-level and patch-level segmentation masks for the signatures on the checks. The images of bank checks were obtained from different sources, including other publicly available check datasets, publicly available images on the internet, as well as scans and images of real checks. Using the GIMP graphics software, pixel-level segmentation masks for signatures on these checks were manually generated as binary images. An automated script was then used to generate patch-level masks. The dataset was created to train and test networks for extracting signatures from bank checks and other similar documents with very complex backgrounds.