A Study on Offline Handwritten Character Recognition (OHCR) of Devanagari Script

Authors

  • Rajesh D. Wagh Computer Science and Engineering, SYCET/Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
  • Swapnil D. Kurhe Computer Science and Engineering, SYCET/Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India

DOI:

https://doi.org/10.37591/joosd.v1i2.267

Keywords:

handwritten character recognition (HCR), Devanagari script, classifiers, benchmark

Abstract

Handwritten Character Recognition (HCR) has been an interesting and challenging area for the researchers and plays an important role in the modern world. Devanagari script contains many Indian languages such as Hindi, Marathi, Rajasthani. All these languages are based on Devanagari script. In this paper, we give an overview on different classifiers (to get the idea of recognition results) and provide new benchmark for future research from the existing systems, for the recognition of offline Devnagari handwritten characters.

References

Saraf V. “Offline Handwritten Character Recognition of Devanagari script uses Genetic Algorithm for Improve efficiency.” ICCSE. 2013: 161–4p.

Pawar VR, Gaikwad A. “Multistage Recognition Approach for Offline Handwritten Marathi Script Recognition.” Int J of Signal Processing, Image Processing and Pattern Recog. 2014; 7(1): 365–78p.

Aggarwal A, Rani R, Dhir R. Handwritten Devanagari Character Recognition Using Gradient Features. IJ ARCSSE. 2012; 2(5): 85–90p.

Sharma N, Pal U, Kimura F, Pal S. ICVGIP 2006, LNCS 4338. 2006: 805–16p.

Agarwal S, Hemarjani N. “Offline Handwritten Character Recognition with Devnagari Script.” IOSR J of Comput Eng. 2013; 12(2): 82–6p.

Singh G, Lehri S. “Recognition of Handwritten Hindi Characters using Backpropagation Neural Network.” IJCSIT. 2012; 3(4): 4892–5p.

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Published

2015-01-08

Issue

Vol. 1 No. 2 (2014)

Section

Research Articles

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