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Neural Computing and Applications

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01.07.2016 | Original Article

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

verfasst von: Manoj Kumar Sharma, Vijay Pal Dhaka

Erschienen in: Neural Computing and Applications | Ausgabe 5/2016

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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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Titel: Segmentation of english Offline handwritten cursive scripts using a feedforward neural network
verfasst von: Manoj Kumar Sharma
Vijay Pal Dhaka
Publikationsdatum: 01.07.2016
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 5/2016
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-015-1940-x

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