Script independent offline writer identification from handwriting samples based on texture using wavelet transform in Persian-English languages

Document Type : Computer Article

Authors

1 Department of Computer Engineering, Birjand University of Technology, Birjand, Iran

2 Department of Computer Engineering, Islamic Azad University, Birjand

3 Department of Computer Engineering, Qatar University, Qatar

Abstract

Recent advances in information technology and the need for more security have led to the rapid development of intelligent biometric identification systems. Recent studies have proven that handwriting of each person is unique and can be used as one of the authentication methods. There are many researches in the literature for writer identification on a specific language. Unfortunately, there are no necessary data sets for this purpose. In this paper, for the first time, a handwritten data set of 300 persons in both Persian and English languages was collected. The main goal of this paper is to provide a model to identify the writer independent of the language written in Persian and English. After pre-processing stage, each person's handwriting is converted into blocks of a certain size called a texture. Then, using these textures, the desired features are extracted. In order to extract these features, first a two-dimensional wavelet transform is applied to each image and then, using the new algorithm for calculating the fractal dimension, which is used for the first time in this field, the feature vector is obtained. Finally, MLP neural networks are utilized for classification step. The performance of the proposed method is evaluated in different scenarios.

Keywords

References

 
[1]       M. K. Sharma and V. Chanderiya, "Writer identification using graphemes", Sādhanā, Vol. 45, No. 1, p. 42, 2020.
[2]       C. Fuglsby, C. P. Saunders, and J. Buscaglia, "U-statistics for estimating performance metrics in forensic handwriting analysis", Journal of Statistical Computation and Simulation, Vol. 90, No. 6, pp. 1082-1117, 2020.
[3]       K. Chaudhari and A. Thakkar, "Survey on handwriting-based personality trait identification", Expert Systems with Applications, Vol. 124, pp. 282-308, 2019.
[4]       Z.-R. Wang, J. Du, and J.-M. Wang, "Writer-aware CNN for parsimonious HMM-based offline handwritten Chinese text recognition", Pattern Recognition, Vol. 100, p. 107102, 2020.
[5]       S. N. Srihari, S.-H. Cha, H. Arora, and S. Lee, "Individuality of handwriting", Journal of forensic science, Vol. 47, No. 4, pp. 1-17, 2002.
[6]       A. Chahi, Y. Ruichek, and R. Touahni, "Cross multi-scale locally encoded gradient patterns for off-line text-independent writer identification", Engineering Applications of Artificial Intelligence, Vol. 89, p. 103459, 2020.
[7]       H. Said, G. Peake, T. Tan, and K. D. Baker, "Writer Identification from Non-uniformly Skewed Handwriting Images", BMVC, pp. 1-10, 1998.
[8]       A. Rehman, S. Naz, M. I. Razzak, and I. A. Hameed, "Automatic visual features for writer identification: a deep learning approach", IEEE access, Vol. 7, pp. 17149-17157, 2019.
[9]       B. Helli and M. E. Moghaddam, "A text-independent Persian writer identification based on feature relation graph (FRG) ", Pattern Recognition, Vol. 43, No. 6, pp. 2199-2209, 2010.
[10]   C. Djeddi, L. Souici-Meslati, and A. Ennaji, "NWriter recognition on arabic handwritten documents", International Conference on Image and Signal Processing, pp. 493-501, Springer, 2012.
[11]   A. Hamadene and Y. Chibani, "One-class writer-independent offline signature verification using feature dissimilarity thresholding", IEEE Transactions on Information Forensics and Security, Vol. 11, No. 6, pp. 1226-1238, 2016.
[12]   Y. Guerbai, Y. Chibani, and B. Hadjadji, "The effective use of the one-class SVM classifier for handwritten signature verification based on writer-independent parameters", Pattern Recognition, Vol. 48, No. 1, pp. 103-113, 2015.
[13]   Y. Kessentini, S. BenAbderrahim, and C. Djeddi, "Evidential combination of SVM classifiers for writer recognition", Neurocomputing, Vol. 313, pp. 1-13, 2018.
[14]   A. Bennour, C. Djeddi, A. Gattal, I. Siddiqi, and T. Mekhaznia, "Handwriting based writer recognition using implicit shape codebook", Forensic science international, Vol. 301, pp. 91-100, 2019.
M. Z. Al-Shamaileh, A. B. Hassanat, A. S. Tarawneh, M. S. Rahman, C. Celik, and M. Jawthari, "New Online/Offline text-dependent arabic handwriting dataset for writer authentication and identification," 2019 10th International Conference on Information and Communication Systems (ICICS), pp. 116-121,2019.
[15]   H. T. Nguyen, C. T. Nguyen, T. Ino, B. Indurkhya, and M. Nakagawa, "Text-independent writer identification using convolutional neural network", Pattern Recognition Letters, Vol. 121, pp. 104-112, 2019.
[16]   Y.-J. Xiong, L. Liu, S. Lyu, P. S. Wang, and Y. Lu, "Improving Text-Independent Chinese Writer Identification with the Aid of Character Pairs", International Journal of Pattern Recognition and Artificial Intelligence, Vol. 33, No. 02, pp. 1953001, 2019.
[17]   C. Djeddi, I. Siddiqi, L. Souici-Meslati, and A. Ennaji, "Text-independent writer recognition using multi-script handwritten texts", Pattern Recognition Letters, Vol. 34, No. 10, pp. 1196-1202, 2013.
[18]   D. Bertolini, L. S. Oliveira, and R. Sabourin, "Multi-script writer identification using dissimilarity", IEEE International Conference on Pattern Recognition (ICPR), pp. 3025-3030, 2016.
[19]   Z. He, X. You, L. Zhou, Y. Cheung, and J. Du, "Writer identification using fractal dimension of wavelet subbands in gabor domain", Integrated Computer-Aided Engineering, Vol. 17, No. 2, pp. 157-165, 2010.
[20]   P. Singh, P. P. Roy, and B. Raman, "Writer identification using texture features: A comparative study", Computers & Electrical Engineering, Vol. 71, pp. 1-12, 2018.
[21]   S. He, and L. Schomaker, "Deep adaptive learning for writer identification based on single handwritten word images", Pattern Recognition, Vol. 88, pp. 64-74, 2019.
[22]   H. T. Nguyen, C. T. Nguyen, T. Ino, B. Indurkhya, and M. Nakagawa, "Text-independent writer identification using convolutional neural network", Pattern Recognition Letters, Vol. 121, pp. 104-112, 2019.
[23]   D. Bertolini, L. S. Oliveira, E. Justino, and R. Sabourin, "Texture-based descriptors for writer identification and verification," Expert Systems with Applications, Vol. 40, No. 6, pp. 2069-2080, 2013.
[24]   N. Otsu, "A threshold selection method from gray-level histograms," IEEE transactions on systems, man, and cybernetics, Vol. 9, No. 1, pp. 62-66, 1979.
[25]   I. Daubechies, "Ten lectures on wavelets", SIAM, 1992.
[26]      سکینه اسدی امیری و حمید حسن پور، "ارائه روشی برای پیش‎پردازش تصویر جهت بهبود عملکرد JPEG 2000 در فشرده‎سازی تصویر"، مدل سازی در مهندسی، دوره 15 شماره 48، سال 1396، صفحه 258-247.
[27]      سید امیر فرهاد قاضی میرسعید; محسن معدنی و مهدی زارع،"بهبود سیستم پایش سلامت سازه در شناسایی محل ترک‌های ریز تیر با استفاده از تبدیل موجک و فیلتر دیجیتال"، مدل سازی در مهندسی، دوره 17 شماره 58، سال 1398، صفحه 316-305.
[28]      امیر عزالدین، حسین نادرپور، علی خیرالدین و غلامرضا قدرتی امیری، "تشخیص محل و میزان ترک در تیرها با استفاده از تبدیل موجک"، مدل­سازی در مهندسی، دوره 12 شماره 39، سال 1393، صفحه  1-11.
[29]   Y. Akbari, K. Nouri, J. Sadri, C. Djeddi, and I. Siddiqi, "Wavelet-based gender detection on off-line handwritten documents using probabilistic finite state automata", Image and Vision Computing, Vol.59, pp. 17-30, 2017.
[30]   L. V. D.Maaten, and G. Hinton, "Visualizing data using t-SNE", Journal of machine learning research, pp. 2579-2605, 2008.
[31]      فاطمه کریمی زاد گوهری و اکبر شاهسوند، "مقایسه نتایج حاصل از شبکه‏­های عصبی MLP و RBF در پیش‌بینی نتایج حاصل از همزمانی پدیده‏­های انتقال جرم و انتقال حرارت"مدل­سازی در مهندسی  دوره 11 شماره 33، سال 1392، صفحه  27-43.
[32]   G. Koch and G. Koch, "Siamese Neural Networks for One-Shot Image Recognition", University of Toronto, 2015.
[33]   E. Hoffer and N. Ailon, "Deep metric learning using triplet network", Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), Vol. 9370, No. 2010, pp. 84–92, 2015.
Journal of Modeling in Engineering
Volume 18, Issue 63
December 2020
Pages 1-13

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History

  • Receive Date: 14 November 2020
  • Revise Date: 10 December 2020
  • Accept Date: 04 January 2021

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