Paper
8 February 2015 Separation of text and background regions for high performance document image compression
Wei Fan, Jun Sun, Satoshi Naoi
Author Affiliations +
Proceedings Volume 9402, Document Recognition and Retrieval XXII; 94020K (2015) https://doi.org/10.1117/12.2075416
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
We describe a document image segmentation algorithm to classify a scanned document into different regions such as text/line drawings, pictures, and smooth background. The proposed scheme is relatively independent of variations in text font style, size, intensity polarity and of string orientation. It is intended for use in an adaptive system for document image compression. The principal parts of the algorithm are the generation of the foreground and background layers and the application of hierarchical singular value decomposition (SVD) in order to smoothly fill the blank regions of both layers so that the high compression ratio can be achieved. The performance of the algorithm, both in terms of its effectiveness and computational efficiency, was evaluated using several test images and showed superior performance compared to other techniques.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Fan, Jun Sun, and Satoshi Naoi "Separation of text and background regions for high performance document image compression", Proc. SPIE 9402, Document Recognition and Retrieval XXII, 94020K (8 February 2015); https://doi.org/10.1117/12.2075416
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Image compression

Image segmentation

Image processing

Binary data

Image resolution

Stationary wavelet transform

Visualization

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