Abstract
Study on behavioural biometric has gained renewed interest from researchers in recent years. Writer identification and verification is one of the areas that has promising prospect in real-life applications like forensic, security, access control, HOCR (Handwritten Optical Character Recognizer), etc. We could not find any complete system for writer identification/verification on Indic scripts including Bangla. In this proposed method, we have modified and evaluated the performance of FFT (Fast Fourier Transform), GLCM (Gray-Level Co-occurrence Matrix), DCT (Discrete Cosine Transform) on our general unconstrained Bangla character database. The database is a collection of total 53250 Bangla characters (38250 alphabets + 7500 Bangla numerals + 7500 Bangla vowel modifiers) from 150 writers with 5 sets from each writer. Modification on FFT, GLCM and DCT to use as textural features and combination of those features produces promising results. The results show that our method is comparable with other available works and capable of handling large volume of data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Azari, B.: Automatic handwriting identification based on the external properties of the samples. IEEE Trans. Syst. Man Cybern. 13(4), 635–642 (1983)
Zimmerman, K., Varady, M.: Handwriter identification from one-bit quantized pressure patterns. Pattern Recognit. 18(1), 63–72 (1985)
Plamondon, R., Lorette, G.: Automatic signature verification and writer identification—the state of the art. Pattern Recognit. 22(2), 107–131 (1989)
Said, H.E.S., Tan, T.N., Baker, K.D.: Personal identification based on handwriting. Pattern Recognit. 33(1), 149–160 (2000)
Marti, U.V., Messerli, R., Bunke, H.: Writer identification using text line based features. In: 6th ICDAR, pp. 101–105 (2001)
Srihari, S.N., Cha, S.H., Arora, H., Lee, S.: Individuality of handwriting. J. Forensic Sci. 47(4), 1–17 (2002)
Bensefia, A., Paquet, T., Heutte, L.: Information retrieval based writer identification. In: 7th ICDAR, pp. 946–950 (2003)
Bulacu, M., Schomaker, L.: Text-independent writer identification and verification using textural and allographic features. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 701–717 (2007)
Bulacu, M., Schomaker, L., Brink, A.: Text-independent writer identification and verification on offline Arabic handwriting. In: 9th ICDAR, pp. 769–773 (2007)
Al-Maadeed, S., Mohammed, E., AlKassis, D., Al-Muslih, F.: Writer identification using edge-based directional probability distribution features for Arabic words. In: AICCSA, pp. 582–590 (2008)
He, Z., You, X., Tang, Y.Y.: Writer identification of Chinese handwriting documents using hidden Markov tree model. IEEE Trans. Pattern Recognit. 41(4), 1295–1307 (2008)
Fiel, S., Sablatnig, R.: Writer retrieval and writer identification using local features. In: 10th IAPR International Workshop on DAS, pp. 145–149 (2012)
Djeddi, C., Siddiqi, I., Souici-Meslati, L., Ennaji, A.: Text-independent writer recognition using multi-script handwritten texts. Pattern Recognit. Lett. 34, 1196–1202 (2013)
Jain, R., Doermann, D.: Writer Identification using an alphabet of contour gradient descriptors. In: 12th ICDAR, pp. 550–554 (2013)
Halder, C., Thakur, K., Phadikar, S., Roy, K.: Writer identification from handwritten Devanagari script. In: 2nd INDIA, pp. 497–505 (2015)
Chanda, S., Franke, K., Pal, U., Wakabayashi, T.: Text independent writer identification for Bengali script. In: 20th ICPR, pp. 2005–2008 (2010)
Halder, C., Roy, K.: Individuality of isolated Bangla numerals. J. Netw. Innov. Comput. 1, 33–42 (2013)
Halder, C., Roy, K.: Individuality of isolated Bangla characters. In: ICDCCom, pp. 1–6 (2014)
Fan, R.E., Chang, K.W., Hsieh, C.J., Wang, X.R., Lin, C.J.: Liblinear: a library for large linear classification. J. Mach. Learn. Res. 9, 1871–1874 (2008)
Acknowledgments
One of the author would like to thank Department of Science and Technology (DST) for support in the form of INSPIRE fellowship.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Halder, C., Obaidullah, S.M., Roy, K. (2016). Offline Writer Identification from Isolated Characters Using Textural Features. In: Das, S., Pal, T., Kar, S., Satapathy, S., Mandal, J. (eds) Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA) 2015. Advances in Intelligent Systems and Computing, vol 404. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2695-6_20
Download citation
DOI: https://doi.org/10.1007/978-81-322-2695-6_20
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2693-2
Online ISBN: 978-81-322-2695-6
eBook Packages: EngineeringEngineering (R0)