Handwritten Chinese Signature Detection on Scanned Technical Documents for Authenticity Verification

Signature detection is one of the crucial predecessor procedures to prove the authenticity of handwritten signatures. Despite the increasing demand for automatedly verifying the signatures on contracts, bills, reports, etc., the research based on signature detection is very limited. One of the imped...

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Bibliographic Details
Published in2022 IEEE International Conference on e-Business Engineering (ICEBE) pp. 240 - 245
Main Authors Zhang, Ying, Zhang, Jian, Yan, Kaihong, Wang, Hongwei, Wang, Gaoang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2022
Subjects
Copy-Paste augmentation
Data models
Data privacy
Detectors
Handwriting recognition
Object detection
Prototypes
signature detection
Training
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Summary:Signature detection is one of the crucial predecessor procedures to prove the authenticity of handwritten signatures. Despite the increasing demand for automatedly verifying the signatures on contracts, bills, reports, etc., the research based on signature detection is very limited. One of the impediments to signature detection is the lack of public annotated datasets due to the interests of privacy and confidentiality. In this paper, we explore a data augmentation method, the Copy-Paste augmentation, to alleviate the scarcity of signed documents. Modeling signature detection as an object detection task, we experiment on Chinese technical documents using different object detection models. The experiment shows that YOLOv5 with Copy-Paste augmentation performs best. Based on the experiment, we propose a prototype system for signature detection.
DOI:10.1109/ICEBE55470.2022.00049