Abstract
Offline handwritten character recognition is the process of recognizing given characters from the large set of characters. OCR system mainly focuses on the recognition of printed or handwritten characters of a scanned image. The proposed system extracts features that are based only on gradient of image which is helpful in exact recognition of characters. A technique to recognize handwritten Devanagari characters using combination of quadratic and SVM classifiers is presented in this paper. Features used are directional features that are strength, angle and histogram of gradient (SOG, AOG, HOG). Using a Gaussian filter, the strength and the angle features are down sampled to obtain a feature vector of 392 dimensions. These features are finally concatenated with HOG feature. Applying these to the combination of quadratic and SVM classifiers to obtain maximum accuracy of 95.81% using 3 fold cross validation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Plamondon, R., Srihari, S.N.: Online and off-line handwriting recognition: a comprehensive survey. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 63–84 (2000)
Pal, U., Chaudhuri, B.B.: Indian script character recognition: a survey. Pattern Recognit. 37(9), 1887–1899 (2004)
Liu, C.-L., Suen, C.Y.: A new benchmark on the recognition of handwritten Bangla and Farsi numeral characters. Pattern Recognit. 42(12), 3287–3295 (2009)
Vaidya, M., Joshi, Y.V.: Handwritten numeral identification system using pixel level distribution features, Smart Innovations, Systems and Technologies, vol. 2, pp. 307–315. Springer publishing (2017)
Gupta, D., and Madhu Nair, L.: Improving Ocr by effective pre-processing and segmentation for Devanagiri script: a quantified study. J. Theor. Appl. Inf. Technol. 52(2), 142–153 (2013)
Shelke, S., Apte, S.: Performance optimization and comparative analysis of neural networks for handwritten Devanagari character recognition. In: Signal and Information Processing (IConSIP), International Conference on. IEEE (2016)
Arica, N., Yarman-Vural, F.T.: An overview of character recognition focused on off-line handwriting. IEEE Trans. Syst. Man, and Cybern. Part C (Applications and Reviews) 31(2), 216–233 (2001)
Roy, P.P., et al.: HMM-based Indic handwritten word recognition using zone segmentation. Pattern Recognit. 60, 1057–1075 (2016)
Vaidya, M.V., Joshi, Y.V.: Marathi numeral recognition using statistical distribution features. In: Information Processing (ICIP), 2015 International Conference on. IEEE (2015)
Kumar, S., Singh, C.: A study of zernike moments and its use in Devanagari handwritten character recognition. In: International Conference on Cognition and Recognition (2005)
Sharma, N., et al.: Recognition of off-line handwritten Devanagari characters using quadratic classifier. In: Computer Vision, Graphics and Image Processing, pp. 805–816. Springer, Berlin (2006)
Pal, U., et al.: Off-line handwritten character recognition of devnagari script. In: Ninth International Conference on Document Analysis and Recognition, 2007. ICDAR 2007, Vol. 1. IEEE (2007)
Shi, Cun-Zhao, et al. Stroke detector and structure based models for character recognition: a comparative study. IEEE Trans. Image Process. 24(12), 4952–4964 (2015)
Pal, Umapada, et al.: Accuracy improvement of Devnagari character recognition combining SVM and MQDF. In: Proceedings of 11th International Conference on Frontiers Handwriting and Recognition (2008)
Pal, U., Wakabayashi, T., Kimura, F.: Comparative study of Devanagari handwritten character recognition using different feature and classifiers. In: Document Analysis and Recognition, 2009. ICDAR’09. 10th International Conference on. IEEE (2009)
Holambe, A.N., Thool, R.C., Jagade, S.M.: Printed and handwritten character & number recognition of devanagari script using gradient features. Int. J. Comput. Appl. 2(9), 975–8887 (2010)
Jangid, M.: Devanagari isolated character recognition by using statistical features. Int. J. Comput. Sci. Eng. 3(2), 2400–2407 (2011)
Singh, G., Lehri, S.: Recognition of handwritten hindi characters using backpropagation neural network. Int. J. Comput. Sci. Inf. Technol. 3(4), 4892–4895 (2012)
Vaidya, M., Joshi, Y.V., Bhalerao, M.: Marathi numeral identification system in Devanagari script using discrete cosine transform. Int. J. Intell. Eng. Syst. 10(6), 78–86 (2017)
Rehman, A., et al.: Simple and effective techniques for core-region detection and slant correction in offline script recognition. In: Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on. IEEE (2009)
Blumenstein, M., Cheng, C.K., Liu, X.Y.: New preprocessing techniques for handwritten word recognition. In: Proceedings of the Second IASTED International Conference on Visualization, Imaging and Image Processing (VIIP 2002), ACTA Press, Calgary (2002)
Pastor, M., Toselli, A., Vidal, E.: Projection profile based algorithm for slant removal. Image Analysis and Recognition, pp. 183–190 (2004)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)
Sinha, R.M.K., Mahabala, H.N.: Machine recognition of Devanagari script. IEEE Trans. Syst. Man Cybern 9(8), 435–441 (1979)
Arora, S., et al.: Combining multiple feature extraction techniques for handwritten devanagari character recognition. In: Industrial and Information Systems, 2008. ICIIS 2008. IEEE Region 10 and the Third international Conference on. IEEE (2008)
Kumar, M., Jindal, M.K., Sharma, R.K.: Segmentation of isolated and touching characters in offline handwritten gurmukhi script recognition. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 6(2), 58 (2014)
Kamble, P.M., Hegadi, R.S.: Handwritten Marathi character recognition using R-HOG Feature. Proc. Comput. Sci. 45, 266–274 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Bhalerao, M., Bonde, S., Nandedkar, A., Pilawan, S. (2018). Combined Classifier Approach for Offline Handwritten Devanagari Character Recognition Using Multiple Features. In: Hemanth, D., Smys, S. (eds) Computational Vision and Bio Inspired Computing . Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71767-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-71767-8_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-71766-1
Online ISBN: 978-3-319-71767-8
eBook Packages: EngineeringEngineering (R0)