Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Identity-Based Combined Public Key Schemes for Signature, Encryption, and Signcryption Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

DFA-Based Online Bangla Character Recognition

verfasst von : Shibaprasad Sen, Dwaipayan Shaoo, Mridul Mitra, Ram Sarkar, Kaushik Roy

Erschienen in: Information Technology and Applied Mathematics

Verlag: Springer Singapore

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In the present experiment, we have investigated the effectiveness of two handcrafted feature extraction techniques for the recognition of constituent strokes of online handwritten Bangla character samples. These techniques estimate local and global shape information from a stroke sample. Combined feature vector is fed to Multi-Layer Perceptron (MLP)-based classifier for stroke recognition purpose. We have achieved 91.27% recognition accuracy over test set. In the current experiment, total size of the stroke database is 32,534. Among the samples, 30% of the entire strokes are considered as test set and rest are used to train the recognition model. Afterward, we have implemented a Deterministic Finite Automata (DFA)-based character recognition system from the recognized strokes. Final outcome of the system is satisfactory considering the stroke variation orders while writing Bangla characters.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel A New Dual Image-Based Steganographic Scheme for Authentication and Tampered Detection Using (7, 4) Hamming Code
Nächstes Kapitel An Integrated Imperfect Production–Inventory Model with Optimal Vendor Investment and Backorder Price Discount
Literatur
1.
Sharma, A., Kumar, R., Sharma, R.K.: Online handwritten Gurmukhi character recognition using elastic matching. In: Congress on Image and Signal Processing, pp. 391–396. IEEE (2008)
2.
Sharma, A., Kumar, R., Sharma, R.K.: HMM-based online handwritten Gurmukhi character recognition. Int. J. Mach. Graph. Vis. 19, 439–440 (2010)
3.
Bawa, R.K., Rani, R.: A preprocessing technique for recognition of online handwritten Gurmukhi numerals. In: IEEE International Conference on High Performance Architecture and Grid Computing, pp. 275–281 (2011)
4.
Sachan, M.K., Lehal Singh, G., Jain, V.K.: A system for online Gurmukhi script recognition. In: Intrernational Conference on Information Systems for Indian Languages, pp. 299–300 (2011)
5.
Swethalakshmi, H., Jayaraman, A., Chakravarthy, V.S., Sekhar, C.C.: On-line handwritten character recognition for Devanagari and Telugu scripts using support vector machines. In: Proceedings of International Workshop on Frontiers in Handwriting Recognition, pp. 367–372 (2006)
6.
Swethalakshmi, H., Sekhar, C.C., Chakravarthy, V.S.: Spatio structural features for recognition of online handwritten characters in Devanagari and Tamil scripts. In: Proceedings of International Conference on Artificial Neural Networks, pp. 230–239 (2007)
7.
Santosh, K.C., Iwata, J.: Stroke-based cursive character recognition. Xiaoqing Ding, INTECH (2012)
8.
Santosh, K.C., Nattee, C., Lamiroy, B.: Relative positioning of stroke-based clustering: a new approach to online handwritten devanagari character recognition. Int. J. Image Graph. 12(2), 25 (2012)
9.
Connell, S.D., Sinha, R.M.K., Jain, A.K.: Recognition of unconstrained online Devanagari characters. In: 5th International Conference on Pattern Recognition, pp. 368–371 (2000)
10.
Joshi, N., Sita, G., Ramakrishnan, A.G., Deepu, V.: Machine recognition of online handwritten Devanagari characters. In: Proceedings of International Conference on Document Analysis and Recognition, pp. 1156–1160 (2005)
11.
Santosh, K.C., Wendlingc, L.: Character recognition based on non-linear multi-projection profiles measure. Int. J. Front. Comput. Sci. 9(5), 678–690 (2015)
12.
Tappert, C.C., Suen, C.Y., Wakahara, T.: The state of online handwriting recognition. In: Transaction on Pattern Analysis and Machine Intelligence, pp. 787–807. IEEE (1990)
13.
Farha, M., Srinivasa, G., Ashwini, A.J., Hemant, K.: Online handwritten character recognition. Int. J. Comput. Sci. 30–36 (2013)
14.
Alvaro, F., Zanibbi, R.: A shape-based layout descriptor for classifying spatial relationships in handwritten math. In: ACM Symposium on Document Engineering, pp. 123–126 (2013)
15.
Roy, K.: Stroke-database design for online handwriting recognition in Bangla. Int. J. Modern Eng. Res. 2534–2540 (2012)
16.
Roy, K., Sharma, N., Pal, U.: Online Bangla handwriting recognition system. In: International Conference on Advances in Pattern Recognition, pp. 117–122 (2007)
17.
Parui, S.K., Guin, K., Bhattacharya, U., Chaudhuri, B.B.: Online handwritten Bangla character recognition using HMM. In: International Conference on Pattern Recognition, pp. 1–4 (2008)
18.
Bhattacharya, U., Gupta, B.K., Parui, S.K.: Direction code based features for recognition of online handwritten characters of Bangla. In: International Conference on Document Analysis and Recognition, pp. 58–62 (2007)
19.
Sen, S.P., Sarkar, R., Roy, K., Hori, N.: Recognize online handwritten Bangla characters using hausdorff distance based feature. In: \(5\)th International Conference on Frontiers in Intelligent Computing: Theory and Application, pp. 541–549 (2017)
20.
Sen, S.P., Mitra, M., Chowdhury, S., Sarkar, R., Roy, K.: Quad-tree based image segmentation and feature extraction to recognize online handwritten Bangla characters. In: \(7\)th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, Ulm, Germany, pp. 246–256 (2016)
21.
Ghosh, R.: A novel feature extraction approach for online Bengali and Devanagari character recognition. In: International Conference on Signal Processing and Integrated Networks, pp. 483–488 (2015)
22.
Sen, S.P., Sarkar, R., Roy, K.: An approach to stroke-based online handwritten Bangla character recognition. In: \(3\)rd International Doctoral Symposium on Applied Computation and Security Systems (2016)
23.
Sen, S.P., Sarkar, R., Roy, K.: A simple and effective technique for online handwritten Bangla character recognition. In: \(4\)th International Conference on Frontiers in Intelligent Computing: Theory and Application, pp. 201–209 (2015)
Metadaten
Titel
DFA-Based Online Bangla Character Recognition
verfasst von
Shibaprasad Sen
Dwaipayan Shaoo
Mridul Mitra
Ram Sarkar
Kaushik Roy
Copyright-Jahr
2019
Verlag
Springer Singapore
Buch
Information Technology and Applied Mathematics

Print ISBN: 978-981-10-7589-6

Electronic ISBN: 978-981-10-7590-2

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-981-10-7590-2_13

Premium Partner

    Bildnachweise