Handwritten Documents Validation Using Pattern Recognition and Transfer Learning

Jadli Aissam, Mustapha Hain and Adil Chergui
Additional contact information
Jadli Aissam: University of Hassan II, Casablanca, Morocco
Mustapha Hain: ENSAM, University of Hassan II, Casablanca, Morocco
Adil Chergui: ENSAM, University of Hassan II, Casablanca, Morocco

International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 2022, vol. 17, issue 5, 1-13

Abstract: Handwritten documents in an Enterprise Resource Planning (ERP) system can come from different sources and usually have different designs, sizes, and subjects (i.e. bills, checks, invoices, etc.). Given these documents were filled manually, they have to be inspected to detect various kinds of issues (missing signature or stamp, missing name, etc.) before being saved in the ERP system or processed by an OCR engine. In this paper, the authors present a transfer learning approach to detect issues in scanned handwritten documents, using an award-winning deep convolutional neural network (InceptionV3) and different machine learning algorithms such as Logistic Regression (LR), Support Vector Machine (SVM) and Naive Bayes (NB). The experiment shows that the combination of InceptionV3 and LR got an accuracy of 91.8% for missing stamp detection. This can allow using this approach in an ERP system as an automatic verification procedure in a document processing flow.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... /IJWLTT.20220901.oa1 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jwltt0:v:17:y:2022:i:5:p:1-13

Access Statistics for this article

International Journal of Web-Based Learning and Teaching Technologies (IJWLTT) is currently edited by Mahesh S. Raisinghani

More articles in International Journal of Web-Based Learning and Teaching Technologies (IJWLTT) from IGI Global
Bibliographic data for series maintained by Journal Editor ().