Handwriting feature extraction method for writer verification independent of character type by using AdaBN and AdaIN

Kimiya Murase; Shunsuke Nakatsuka; Mariko Hosoe; Kunihito Kato

doi:10.1117/12.2567065

1 June 2020 Handwriting feature extraction method for writer verification independent of character type by using AdaBN and AdaIN

Kimiya Murase, Shunsuke Nakatsuka, Mariko Hosoe, Kunihito Kato

Author Affiliations +

Proceedings Volume 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020; 1151504 (2020) https://doi.org/10.1117/12.2567065
Event: International Workshop on Advanced Imaging Technologies 2020 (IWAIT 2020), 2020, Yogyakarta, Indonesia

Abstract

Writer verification is usually conducted by checking similarity between same type characters written by known and unknown writers. However, in the case where the same type characters do not exist in each writer’s documents, writer verification is very difficult. In this paper, we propose a method to extract the handwriting features independent of character types to solve this problem. The proposed model is based on AutoEncoder, and applying Adaptive Batch Normalization (AdaBN) and Adaptive Instance Normalization (AdaIN) for each layer of Encoder or Decoder to extract the objective features. We conducted a writer verification experiment using handwriting images pairs between different character types of ETL-1 Character Database (ETL-1). As a result of the experiment, we confirmed that the proposed method could perform writer verification with high accuracy even in such a case.

Citation Download Citation

Kimiya Murase, Shunsuke Nakatsuka, Mariko Hosoe, and Kunihito Kato "Handwriting feature extraction method for writer verification independent of character type by using AdaBN and AdaIN", Proc. SPIE 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020, 1151504 (1 June 2020); https://doi.org/10.1117/12.2567065

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