Paper
19 January 2009 Hardware-friendly mixed content compression algorithm
Author Affiliations +
Proceedings Volume 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications; 724114 (2009) https://doi.org/10.1117/12.805965
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
The mixed content compression (MCC) algorithm developed in this research provides a hardware efficient solution for compression of scanned compound document images. MCC allows for an easy implementation in imaging pipeline hardware by using only an 8 row buffer of pixels. MCC uses the JPEG encoder to effectively compress the background and picture content of a document image. The remaining text and line graphics in the image, which require high spatial resolution, but can tolerate low color resolution, are compressed using a JBIG1 encoder and color quantization. To separate the text and graphics from the image, MCC uses a simple mean square error (MSE) block classification algorithm to allow a hardware efficient implementation. Results show that for our comprehensive training suite, the compression ratio average achieved by MCC was 60:1, but JPEG only achieved 35:1. In particular, MCC compression ratios become very high on average (82:1 versus 44:1) for mono text documents, which are very common documents being copied and scanned with all-in-ones. In addition, MCC has an edge sharpening side-effect that is very desirable for the target application.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maribel Figuera, Peter Majewicz, and Charles A. Bouman "Hardware-friendly mixed content compression algorithm", Proc. SPIE 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications, 724114 (19 January 2009); https://doi.org/10.1117/12.805965
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image compression

Computer programming

Visualization

Binary data

Quantization

Image classification

Image segmentation

RELATED CONTENT

Embedding digital data on paper in iconic text
Proceedings of SPIE (April 03 1997)
Rate-distortion-based segmentation for MRC compression
Proceedings of SPIE (December 28 2001)
Flexible network document imaging architecture
Proceedings of SPIE (December 20 1999)
Color, complex document segmentation and compression
Proceedings of SPIE (April 03 1997)
Progressive geometry encoder based on the octree structure
Proceedings of SPIE (January 18 2004)

Back to Top