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.

Date Published: 8 February 2015
PDF: 12 pages
Proc. SPIE 9402, Document Recognition and Retrieval XXII, 94020K (8 February 2015); doi: 10.1117/12.2075416

Published in SPIE Proceedings Vol. 9402:
Document Recognition and Retrieval XXII
Eric K. Ringger; Bart Lamiroy, Editor(s)