Text extraction via an edge-bounded averaging and a parametric character model

Jian Fan

doi:10.1117/12.472839

13 January 2003 Text extraction via an edge-bounded averaging and a parametric character model

Jian Fan

Proceedings Volume 5010, Document Recognition and Retrieval X; (2003) https://doi.org/10.1117/12.472839
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

We present a deterministic text extraction algorithm that relies on three basic assumptions: color/luminance uniformity of the interior region, closed boundaries of sharp edges and the consistency of local contrast. The algorithm is basically independent of the character alphabet, text layout, font size and orientation. The heart of this algorithm is an edge-bounded averaging for the classification of smooth regions that enhances robustness against noise without sacrificing boundary accuracy. We have also developed a verification process to clean up the residue of incoherent segmentation. Our framework provides a symmetric treatment for both regular and inverse text. We have proposed three heuristics for identifying the type of text from a cluster consisting of two types of pixel aggregates. Finally, we have demonstrated the advantages of the proposed algorithm over adaptive thresholding and block-based clustering methods in terms of boundary accuracy, segmentation coherency, and capability to identify inverse text and separate characters from background patches.

Citation Download Citation

Jian Fan "Text extraction via an edge-bounded averaging and a parametric character model", Proc. SPIE 5010, Document Recognition and Retrieval X, (13 January 2003); https://doi.org/10.1117/12.472839

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