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EAU-Net: A New Edge-Attention Based U-Net for Nationality Identification

Pal Choudhury, Aritro; Shivakumara, Palaiahnakote; Pal, Umapada; Liu, Cheng-Lin

Authors

Aritro Pal Choudhury

Umapada Pal

Cheng-Lin Liu



Abstract

Identifying crime or individuals is one of the key tasks toward smart and safe city development when different nationals are involved. In this regard, identifying Nationality/Ethnicity through handwriting has received special attention. But due to freestyle and unconstrained writing, identifying nationality is challenging. This work considers words written by people of 10 nationals namely, India, Malaysia, Myanmar, Bangladesh, Iran, Pakistan, Sri Lanka, Cambodia, Palestine, and China, for identification. To extract invariant features, such as the distribution of edge patterns despite of the adverse effect of different writing styles, paper, pen, and ink, we explore a new Edge-Attention based U-Net (EAU-Net), which generates edge points for each input word image written by different nationals. Inspired by the success of the Convolutional Neural Network for classification, we explore CNN for the classification of 10 classes by considering candidate points given by EAU-Net as input. The proposed method is tested on our newly developed dataset of 10 classes, a standard dataset of 5 classes to demonstrate the effectiveness in classifying different nationalities. Furthermore, the efficacy of the proposed method is shown by testing on IAM dataset for gender identification. The results of the proposed and existing methods show that the proposed method outperforms the existing methods for both nationality and gender identification.

Presentation Conference Type Conference Paper (published)
Conference Name Frontiers in Handwriting Recognition, 18th International Conference, ICFHR 2022
Start Date Dec 4, 2022
End Date Dec 7, 2022
Online Publication Date Nov 25, 2022
Publication Date Nov 25, 2022
Deposit Date Nov 15, 2024
Publisher Springer
Pages 137-152
Series Title Lecture Notes in Computer Science
Series Number 13639
Series ISSN 1611-3349
Book Title Frontiers in Handwriting Recognition 18th International Conference, ICFHR 2022, Hyderabad, India, December 4–7, 2022, Proceedings
ISBN 9783031216473
DOI https://doi.org/10.1007/978-3-031-21648-0_10