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A Fuzzy Matching based Image Classification System for Printed and Handwritten Text Documents

A Fuzzy Matching based Image Classification System for Printed and Handwritten Text Documents

Shalini Puri, Satya Prakash Singh
Copyright: © 2020 |Volume: 13 |Issue: 2 |Pages: 40
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781799805465|DOI: 10.4018/JITR.2020040110
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MLA

Puri, Shalini, and Satya Prakash Singh. "A Fuzzy Matching based Image Classification System for Printed and Handwritten Text Documents." JITR vol.13, no.2 2020: pp.155-194. http://doi.org/10.4018/JITR.2020040110

APA

Puri, S. & Singh, S. P. (2020). A Fuzzy Matching based Image Classification System for Printed and Handwritten Text Documents. Journal of Information Technology Research (JITR), 13(2), 155-194. http://doi.org/10.4018/JITR.2020040110

Chicago

Puri, Shalini, and Satya Prakash Singh. "A Fuzzy Matching based Image Classification System for Printed and Handwritten Text Documents," Journal of Information Technology Research (JITR) 13, no.2: 155-194. http://doi.org/10.4018/JITR.2020040110

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Abstract

This article proposes a bi-leveled image classification system to classify printed and handwritten English documents into mutually exclusive predefined categories. The proposed system follows the steps of preprocessing, segmentation, feature extraction, and SVM based character classification at level 1, and word association and fuzzy matching based document classification at level 2. The system architecture and its modular structure discuss various task stages and their functionalities. Further, a case study on document classification is discussed to show the internal score computations of words and keywords with fuzzy matching. The experiments on proposed system illustrate that the system achieves promising results in the time-efficient manner and achieves better accuracy with less computation time for printed documents than handwritten ones. Finally, the performance of the proposed system is compared with the existing systems and it is observed that proposed system performs better than many other systems.

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