Abstract
In this paper, an efficient approach for text-independent writer identification using bag of words model and the combination of multiple classifiers is proposed. First of all, a bag of words model is established by extracting sub-images from the original handwriting image. Then, features are extracted by moment method, direction index histogram method and simplified Wigner method respectively to calculate the distance between the sub images having the same labels. Finally, the handwriting classification task is completed by means of feature fusion and multi-classifier combination. To evaluate this approach, writer identification is conducted on IAM English database. Experimental results revealed that the proposed writer identification algorithm with small number of characters and unconstrained contents achieves interesting results as compared to those reported by the existing writer recognition systems.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Wu, X., Tang, Y., Bu, W.: Offline text-independent writer identification based on scale invariant feature transformation. IEEE Trans. Inf. Forensics Secur. 9(3), 526–536 (2014)
Christlein, V., Gropp, M., Fiel, S., Maier, A.: Unsupervised feature learning for writer identification and writer retrieval. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 991–997 (2018)
Chahi, A., El Merabet, Y., Ruichek, Y., Touahni, R.: An effective and conceptually simple feature representation for off-line text-independent writer identification. Expert Syst. Appl. 123, 357–376 (2019)
Xiao, J., Zou, W., Chen, Y., Wang, W., Lei, J.: Single image rain removal based on depth of field and sparse coding. Pattern Recogn. Lett. 116, 212–217 (2018)
Litifu, A., Yan, Y., Xiao, J., Jiang, H., Yao, W.: Text-independent writer identification based on hybrid codebook and factor analysis [J/OL]. Acta Autom. Sinica 1–11 (2019). https://doi.org/10.16383/j.aas.c190121
Tan, G.J., Sulong, G., Rahim, M.S.M.: Writer identification: a comparative study across three world major languages. Forensic Sci. Int. 279, 41–52 (2017)
Fiel, S., Sablatnig, R.: Writer retrieval and writer identification using local features. In: International Workshop on Document Analysis Systems, pp. 145–149 (2012)
Xiong, Y., Wen, Y., Wang, S., Lu, Y.: Text-independent writer identification using SIFT descriptor and contour-directional feature. In: International Conference on Document Analysis and Recognition, pp. 91–95 (2015)
Khan, F.A., Khelifi, F., Tahir, M.A., Bouridane, A.: Dissimilarity Gaussian mixture models for efficient offline handwritten text-independent identification using SIFT and RootSIFT descriptors. IEEE Trans. Inf. Forensics Secur. 14(2), 289–303 (2019)
Hannad, Y., Siddiqi, I., El Youssfi, M., Kettani, E.: Writer identification using texture descriptors of handwritten fragments. Expert Syst. Appl. 47, 14–22 (2016)
Siddiqi, I., Vincent, N.: Text-independent writer recognition using redundant writing patterns with contour-based orientation and curvature features. Pattern Recogn. 43(11), 3853–3865 (2010)
Ghiasi, G., Safabakhsh, R.: Offline text-independent writer identification using codebook and efficient code extraction methods. Image Vis. Comput. 31, 379–391 (2013)
Khalifa, E., Al-Maadeed, S., Tahir, M.A., Bouridane, A., Jamshed, A.: Off-line writer identification using an ensemble of grapheme codebook features. Pattern Recogn. Lett. 59(1), 18–25 (2015)
Khan, F.A., Tahir, M.A., Khelifi, F., Bouridane, A., Almotaeryi, R.: Robust off-line text independent writer identification using bagged discrete cosine transform features. Expert Syst. Appl. 71, 404–415 (2017)
He, S., Schomaker, L.: Writer identification using curvature-free features. Pattern Recogn. 63, 451–464 (2017)
Nguyen, H.T., Nguyen, C.T., Ino, T., Indurkhya, B., Nakagawa, M.: Text-independent writer identification using convolutional neural network. Pattern Recogn. Lett. 121, 104–112 (2019)
Aubin, V., Mora, M., Santos-Peñas, M.: Off-line writer verification based on simple graphemes. Pattern Recogn. 79, 414–426 (2018)
Xiao, J., Tian, H., Zhang, Y., Zhou, Y., Lei, J.: Blind video denoising via texture aware noise estimation. Comput. Vis. Image Underst. 169, 1–13 (2018)
Mirzapour, F., Ghassemian, H.: Moment-based feature extraction from high spatial resolution hyperspectral images. Int. J. Remote Sens. 37(6), 1349–1361 (2016)
Marti, U., Bunke, H.: The IAM-database: an English sentence database for off-line handwriting recognition. Int. J. Doc. Anal. Recogn. 5, 39–46 (2002)
Acknowledgment
This work is supported by University Scientific Research Program Natural Science Youth Project of Xinjiang Uyghur Autonomous Region (Grant No. XJUDU2019Y032), and the Tender Subject for Key Laboratory Project of Xinjiang Normal University (Grant No. XJNUSYS092018A02).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Litifu, A., Yan, Y., Xiao, J., Jiang, H., Yao, W., Wang, J. (2020). Writer Identification Based on Combination of Bag of Words Model and Multiple Classifiers. In: Cree, M., Huang, F., Yuan, J., Yan, W. (eds) Pattern Recognition. ACPR 2019. Communications in Computer and Information Science, vol 1180. Springer, Singapore. https://doi.org/10.1007/978-981-15-3651-9_6
Download citation
DOI: https://doi.org/10.1007/978-981-15-3651-9_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3650-2
Online ISBN: 978-981-15-3651-9
eBook Packages: Computer ScienceComputer Science (R0)