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Segmentation of english Offline handwritten cursive scripts using a feedforward neural network

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Abstract

In the present paper, we used the Pixel Plot and Trace and Re-plot and Re-trace (PPTRPRT) technique for English offline handwritten curve scripts and leads. Unlike other approaches, the PPTRPRT technique prioritizes segmentation of words and characters. The PPTRPRT technique extracts text regions from English offline handwritten cursive scripts and leads an iterative procedure for segmentation of text lines along with skew and de-skew operations. Iteration outcomes provide for pixel space-based word segmentation which enables segmentation of characters. The PPTRPRT technique embraces various dispensations in segmentation of characters from English offline handwritten cursive scripts. Moreover, various normalization steps allow for deviations in pen breadth and inscription slant. Investigational outcomes show that the proposed technique is competent at extracting characters from English offline handwritten cursive scripts.

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  1. Jaipur National University, Jagatpura Jaipur Rajasthan, Jaipur, 302017, India

    Manoj Kumar Sharma & Vijay Pal Dhaka

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  1. Manoj Kumar Sharma
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  2. Vijay Pal Dhaka
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Correspondence to Manoj Kumar Sharma.

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Sharma, M.K., Dhaka, V.P. Segmentation of english Offline handwritten cursive scripts using a feedforward neural network. Neural Comput & Applic 27, 1369–1379 (2016). https://doi.org/10.1007/s00521-015-1940-x

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