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Text and non-text separation in offline document images: a survey

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Abstract

Separation of text and non-text is an essential processing step for any document analysis system. Therefore, it is important to have a clear understanding of the state-of-the-art of text/non-text separation in order to facilitate the development of efficient document processing systems. This paper first summarizes the technical challenges of performing text/non-text separation. It then categorizes offline document images into different classes according to the nature of the challenges one faces, in an attempt to provide insight into various techniques presented in the literature. The pros and cons of various techniques are explained wherever possible. Along with the evaluation protocols, benchmark databases, this paper also presents a performance comparison of different methods. Finally, this article highlights the future research challenges and directions in this domain.

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Notes

  1. Please note that in the literature, the terms region and zone are often used interchangeably, with the term zone being preferred when a region is rectangular. For simplicity however, we will use the term region to mean either zone or polygonal region in this document.

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  1. Jadavpur University, Kolkata, India

    Showmik Bhowmik, Ram Sarkar & Mita Nasipuri

  2. Institute for Advanced Computer Studies, University of Maryland, College Park, USA

    David Doermann

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  1. Showmik Bhowmik
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Correspondence to Ram Sarkar.

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Bhowmik, S., Sarkar, R., Nasipuri, M. et al. Text and non-text separation in offline document images: a survey. IJDAR 21, 1–20 (2018). https://doi.org/10.1007/s10032-018-0296-z

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