Writer age estimation through handwriting

Huang, Zhiheng and Palaiahnakote, Shivakumara and Kaljahi, Maryam Asadzadeh and Kumar, Ahlad and Pal, Umapada and Lu, Tong and Blumenstein, Michael (2023) Writer age estimation through handwriting. Multimedia Tools and Applications, 82 (11). pp. 16033-16055. ISSN 1380-7501, DOI https://doi.org/10.1007/s11042-022-13840-w.

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Handwritten image-based writer age estimation is a challenging task due to the various writing styles of different individuals, use of different scripts, varying alignment, etc. Unlike age estimation using face recognition in biometrics, handwriting-based age classification is reliable and inexpensive because of the plain backgrounds of documents. This paper presents a novel model for deriving the phase spectrum based on the Harmonic Wavelet Transform (HWT) for age classification on handwritten images from 11 to 65 years. This includes 11 classes with an interval of 5 years. In contrast to the Fourier transform, which provides a noisy phase spectrum due to loss of time variations, the proposed HWT-based phase spectrum retains time variations of phase and magnitude. As a result, the proposed HWT-based phase spectrum preserves vital information of changes in handwritten images. In order to extract such information, we propose new phase statistics-based features for age classification based on the understanding that as age changes, writing style also changes. The features and the input images are fed to a VGG-16 model for age classification. The proposed method is tested on our own dataset and three standard datasets, namely, IAM-2, KHATT and that of Basavaraja et al. to demonstrate the effectiveness of the proposed model compared to the existing methods in terms of classification rate. The results of the proposed and existing methods on different datasets show that the proposed method outperforms the existing methods in terms of classification rate.

Item Type: Article
Funders: National Natural Science Foundation of China (NSFC) (Grant No: 61, 672, 273 & 61, 832, 008), Ministry of Education, Malaysia (Grant No: FRGS/1/2020/ICT02/UM/02/4)
Uncontrolled Keywords: Fourier phase spectrum; Harmonic wavelet phase spectrum; Phase statistics; Handwriting analysis; Age estimation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology > Department of Computer System & Technology
Depositing User: Ms Zaharah Ramly
Date Deposited: 27 Nov 2023 04:50
Last Modified: 27 Nov 2023 04:50
URI: http://eprints.um.edu.my/id/eprint/39394

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