Invariant Behavioural based Discrimination for Individual Representation

Wong Yee Leng, Siti Mariyam Shamsuddin, Nor Azman Ismail


Writer identification based on cursive words is one of the areas in pattern recognition that has created a centre of attention by many researchers to work in. Recently, its focal point is in forensic investigation and biometric application as such the writing style can be used as behavioural features for authenticating an author. In this study, a novel approach of presenting cursive features of authors is presented. The invariants-based discriminability of the features is proposed by discretizing the moment features of each writer using Biometric Invariant Discretization Cutting Point (BIDCP). BIDCP is introduced for features perseverance to obtain better individual representations and discriminations. Our experiments have revealed that by using the proposed method, the authorship identification based on cursive words is significantly increased with an average identification rate of 99.80%.


authorship; behavioural biometric; data mining; identification; discretization


S.N. Srihari, C. Huang, H. Srinivasan, V. A.Shah, Biometric and forensic aspects of digital document processing, Digital Document Processing, B. B. Chaudhuri (ed.), Springer, (2006).

L Xiaohong, L. Yuanyuan, "Handwriting identification: Challenges and solutions", J Forensic Sci Med 2018, vol. 4, pp. 167-73.

B, Ameur & T, Hatem, Validity of Handwriting in Biometric Systems. (2018) 5-10.

A. Rehman, S. Naz, M. I. Razzak, "Writer identification using machine learning approaches: A comprehensive review", Multimedia Tools Appl., pp. 1-43, Sep. 2018.

C. Adak, B. B. Chaudhuri, M. Blumenstein, An empirical study on writer identification & verification from intra-variable individual handwriting, 2017, [online] Available:

P. Pandey, K.R. Seeja, A. Somani, S. Srivastava, A. Mundra, S. Rawat, "Forensic Writer Identification with Projection Profile Representation of Graphemes", Proceedings of First International Conference on Smart System Innovations and Computing. Smart Innovation Systems and Technologies, vol. 79, pp. 129-136, 2018.

Rokiah@Rozita Ahmad, Maslina Darus, Siti Mariyam Shamsuddin & Azuraliza Abu Bakar (2004), Pendiskretan Data Set Kasar Menggunakan Ta’akulan Boolean (Rough Set Data Discretization using Boolean Reasoning) , Jurnal Teknologi Maklumat & Multimedia 1(2004): 15-26.

M. Bulacu, L. Schomaker, Combining multiple features for text-independent writer identification and verification, in: 10th International Workshop on Frontiers in Handwriting Recognition (IWFHR 2006), 23 - 26 October, La Baule, France (2006) 281-286.

G. Sami, E.B.A. Najoua, Writer identification using modular MLP classifier and genetic algorithm for optimal features selection, ISNN 2006, LNCS 3972, (2006) 271 – 276.

P. Pandey, K. R. Seeja, "Forensic writer identification with projection profile representation of graphemes", Proc. 1st Int. Conf. Smart Syst. Innov. Comput, pp. 129-136, 2018.

F. Cloppet, V. Eglin, V. C. Kieu, D. Stutzmann, N. Vincent, V. Eglin, V. C. Kieu, D. Stutzmann, N. Vincent, "ICFHR2016 competition on the classification of medieval handwritings in latin script", 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 590-595, oct 2016.

A. Durou, I. Aref, S. Al-Maadeed, A. Bouridane, E. Benkhelifa, "Writer identification approach based on bag of words with OBI features", Inf. Process. Manage., vol. 56, no. 2, pp. 354-366, 2019.

A. A. Ahmed, H. R. Hasan, F. A. Hameed, O. I. Al-Sanjary, "Writer identification on multi-script handwritten using optimum features", Kurdistan J. Appl. Res., vol. 2, no. 3, pp. 178-185, 2017.

S. Fiel, F. Kleber, M. Diem, V. Christlein, G. Louloudis, N. Stamatopou-Los, B. Gatos, "ICDAR 2017 competition on historical document writer identification (Historical-WI)", 2017 14th International Conference on Document Analysis and Recognition, nov 2017

J. J. Miller, R. B. Patterson, D. T. Gantz, C. P. Saunders, M. A. Walch, J. Buscaglia, "A set of handwriting features for use in automated writer identification", J. Forensic Sci., vol. 62, no. 3, pp. 722-734, 2017.

M.K. Hu, Visual pattern recognition by moment invariants, IRE Transaction on Information Theory. 8 (2), (1962) 179-187.

F.L. Alt, Digital pattern recognition by moments, Journal of the ACM (JACM), Volume 9, Issue 2, April (1962) 240 – 258.

T.H. Reiss, The revised fundamental theorem of moment invariants, Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 13, Issue 8, Aug. (1991) 830 – 834.

S.O. Belkasim, M. Shridhar, M. Ahmadi, Pattern recognition with moment invariants: a comparative study and new results, Pattern Recognition, vol. 24 (12), (1991) 1117-1138.

P. Feng, M. Keane, A new set of moment invariants for handwritten numeral recognition, Image Processing, in: ICIP-94, IEEE International Conference Volume 1, 13-16 Nov. (1994) 154 –158.

C.-C. Chen, Improved moment invariants for shape discrimination. Pattern Recognition, Volume 26, Issue 5, May (1993) 683-686.

A.K. Muda, S.M. Shamsuddin, M. Darus, Embedded scale united moment invariant for identification of handwriting individuality, in: ICCSA 2007, LNCS 4705, Springer Verlag, (2007) 385 – 396.

U. Stańczyk, On Unsupervised and Supervised Discretisation in Mining Stylometric Features. In: Gruca A., Czachórski T., Deorowicz S., Harężlak K., Piotrowska A. (eds) Man-Machine Interactions 6. ICMMI 2019. Advances in Intelligent Systems and Computing, vol 1061. Springer, Chamm(2020)

A.K. Muda, S.M. Shamsuddin. and M. Darus, “Invariants Discretization for Individuality Representation in Handwritten Authorship,” International Workshop on Computational Forensic (IWCF 2008), LNCS 5158, Springer Verlag, pp. 218- 228 Digits. International Journal of Computer Mathematics, vol. 74, (2000) 439-447.

T. Suk, J. Flusser, Affine moment invariants Generated by graph method. Pattern Recognition (2010), DOI:10.1016/j.patcog.2010.05.015.

Total views : 0 times

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

ISSN 2088-8708, e-ISSN 2722-2578