Abstract
This paper describes the online Arabic writer identification competition held at ICDAR 2021 Workshop on Arabic and derived Script Analysis and Recognition (ASAR 2021, 4th edition). This first competition of online writer identification uses the ADAB database with online Arabic handwritten words which represent the Tunisian town names. Four systems are participating in the competition. The systems are evaluated on test data that are unknown to the participants. The systems are compared based on the writer identification rate. A detailed description of the systems and the results achieved are presented.
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References
Dhieb, T., Ouarda, W., Boubaker, H., Halima, M.B., Alimi, A.M.: Online Arabic writer identification based on Beta-Elliptic model. In: 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 74–79 (2015)
Dhieb, T., Ouarda, W., Boubaker, H., Alimi, A.M.: Deep neural network for online writer identification using Beta-Elliptic model. In: 2016 International Joint Conference on Neural Networks (IJCNN), pp. 1863–1870 (2016)
Dhieb, T., Ouarda, W., Boubaker, H., Alimi, A.M.: Beta-Elliptic model for writer identification from online Arabic handwriting. J. Inf. Assur. Secur. 11, 263–272 (2016)
Dhieb, T., Njah, S., Boubaker, H., Ouarda, W., Ayed, M.B., Alimi, A.M.: An extended Beta-Elliptic model and fuzzy elementary perceptual codes for online multilingual writer identification using deep neural network. arXiv:1804.05661 (2018)
BabaAli, B.: Online writer identification using statistical modeling-based feature embedding. Soft Comput. 25(14), 9639–9649 (2021). https://doi.org/10.1007/s00500-021-05729-x
Chen, Z., Yu, H.-X., Wu, A., Zheng, W.-S.: Letter-level online writer identification. Int. J. Comput. Vis. 129(5), 1394–1409 (2021). https://doi.org/10.1007/s11263-020-01414-y
Venugopal, V., Sundaram, S.: Online writer identification system using adaptive sparse representation framework. IET Biometrics 9, 126–133 (2020)
Awaida, S.M., Mahmoud, S.A.: State of the art in off-line writer identification of handwritten text and survey of writer identification of Arabic text. ERR 7, 445–463 (2012)
Bulacu, M., Schomaker, L., Brink, A.: Text-independent writer identification and verification on offline Arabic handwriting. In: Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), pp. 769–773 (2007)
Hassen, H., Al-Maadeed, S.: Arabic handwriting recognition using sequential minimal optimization. In: 2017 1st International Workshop on Arabic Script Analysis and Recognition (ASAR), pp. 79–84 (2017)
ElAbed, H., Märgner, V., Kherallah, M., Alimi, A.M.: ICDAR 2009 Online Arabic Handwriting Recognition Competition. In: 2009 10th International Conference on Document Analysis and Recognition, pp. 1388–1392 (2009)
ElAbed, H., Kherallah, M., Märgner, V., Alimi, A.M.: On-line Arabic handwriting recognition competition: ADAB database and participating systems. Int. J. Doc. Anal. Recogn. 14, 15–23 (2011)
Kherallah, M., Tagougui, N., Alimi, A.M., Abed, H.E., Margner, V.: Online Arabic handwriting recognition competition. In: 2011 International Conference on Document Analysis and Recognition, pp. 1454–1458 (2011)
Boubaker, H., Elbaati, A., Tagougui, N., ElAbed, H., Kherallah, M., Alimi, A.M.: Online Arabic databases and applications. In: Märgner, V., El Abed, H. (eds.) Guide to OCR for Arabic Scripts, pp. 541–557. Springer, London (2012). https://doi.org/10.1007/978-1-4471-4072-6_22
Tagougui, N., Kherallah, M., Alimi, A.M.: Online Arabic handwriting recognition: a survey. Int. J. Doc. Anal. Recogn. (IJDAR) 3, 209–226 (2013)
Dhieb, T., Boubaker, H., Ouarda, W., Ayed, M.B., Alimi, A.M.: Deep bidirectional long short-term memory for online Arabic writer identification based on Beta-Elliptic model. In: 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), pp. 35–40 (2019)
Dhieb, T., Njah, S., Boubaker, H., Ouarda, W., Ayed, M.B., Alimi, A.M.: An online writer identification system based on Beta-Elliptic model and fuzzy elementary perceptual codes. arXiv preprint arXiv:1804.05661 (2018)
Dhieb, T., Njah, S., Boubaker, H., Ouarda, W., Ben Ayed, M., Alimi, A.M.: Towards a novel biometric system for forensic document examination. Comput. Secur. 97, 101973 (2020)
Dhieb, T., Boubaker, H., Ouarda, W., Njah, S., Ben Ayed, M., Alimi, A.M.: Deep bidirectional long short-term memory for online multilingual writer identification based on an extended Beta-Elliptic model and fuzzy elementary perceptual codes. Multimedia Tools Appl. 80(9), 14075–14100 (2021). https://doi.org/10.1007/s11042-020-10412-8
Paarmann, L.D. (ed.): Chebyshev type II filters. In: Design and Analysis of Analog Filters: A Signal Processing Perspective, pp. 155–176. Springer, Boston (2001). https://doi.org/10.1007/0-306-48012-3_5
Dhieb, T., Rezzoug, N., Boubaker, H., Gorce, P., Alimi, A.M.: Effect of age on hand drawing movement kinematics. Comput. Methods Biomech. Biomed. Engin. 22, S188–S190 (2019)
Boubaker, H., Chaabouni, A., Kherallah, M., Alimi, A.M., Abed, H.E.: Fuzzy segmentation and graphemes modeling for online Arabic handwriting recognition. In: 2010 12th International Conference on Frontiers in Handwriting Recognition, pp. 695–700 (2010)
Boubaker, H., Kherallah, M., Alimi, A.M.: Optimization of the beta–elliptic model features estimation. In: 16th International Conference of Graphonomix Society (IGS 2013), pp. 151–154. International Graphonomix Society (2013)
Hamdi, Y., Boubaker, H., Dhieb, T., Elbaati, A., Alimi, A.M.: Hybrid DBLSTM-SVM Based Beta-Elliptic-CNN models for online Arabic characters recognition. In: 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 545–550 (2019)
Akouaydi, H., et al.: Neural architecture based on fuzzy perceptual representation for online multilingual handwriting recognition. arXiv:1908.00634 (2019)
Rabhi, B., Elbaati, A., Hamdi, Y., Alimi, A.M.: Handwriting recognition based on temporal order restored by the end-to-end system. In: 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 1231–1236 (2019)
Akouaydi, H., Njah, S., Ouarda, W., Samet, A., Zaied, M., Alimi, A.M.: Convolutional neural networks for online arabic characters recognition with Beta-Elliptic knowledge domain. In: 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), pp. 41–46 (2019)
Rabhi, B., Elbaati, A., Boubaker, H., Hamdi, Y., Hussain, A., Alimi, A.: Temporal order and pen velocity recovery for character handwriting based on sequence-to-sequence with attention mode (2021). https://doi.org/10.36227/techrxiv.13902650.v1
Hamdi, Y., Boubaker, H., Alimi, A.M.: Data augmentation using geometric, frequency, and beta modeling approaches for improving multi-lingual online handwriting recognition. IJDAR (2021). https://doi.org/10.1007/s10032-021-00376-2
Njah, S., Bezine, H., Alimi, A.M.: Linguistic interpretation for on-line handwriting using PerTOHS theory. In: 16th International Graphonomics Society (IGS), pp. 175–178 (2013)
Njah, S., Ltaief, M., Bezine, H., Alimi, A.M.: The PerTOHS theory for on line handwriting segmentation (2012)
Njah, S., Bezine, H., Alimi, A.M.: On-line Arabic handwriting segmentation via perceptual codes: application to MAYASTROUN database. In: Eighth International Multi-Conference on Systems, Signals Devices, pp. 1–5 (2011)
Gordon, I.E.: Theories of Visual Perception. Psychology Press, London (2004)
Acknowledgments
The research leading to these results has received funding from the Ministry of Higher Education and Scientific Research of Tunisia under the grant agreement number LR11ES4.
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Dhieb, T., Boubaker, H., Njah, S., Ben Ayed, M., Alimi, A.M. (2021). ASAR 2021 Online Arabic Writer Identification Competition. In: Barney Smith, E.H., Pal, U. (eds) Document Analysis and Recognition – ICDAR 2021 Workshops. ICDAR 2021. Lecture Notes in Computer Science(), vol 12916. Springer, Cham. https://doi.org/10.1007/978-3-030-86198-8_25
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DOI: https://doi.org/10.1007/978-3-030-86198-8_25
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