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Proceedings Paper

Segmentation for mixed raster contents with multiple extracted constant color areas
Author(s): Zhigang Fan; Timothy Jacobs
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Paper Abstract

Mixed Raster Contents (MRC) is a powerful image representation concept in achieving high compression ratios while maintaining high reconstructed image quality. The Multiple Extracted Constant Color Areas (MECCA) model, which is composed of one contone background layer and multiple constant color foreground layers has the advantages of its ease of decomposition and inherent text enhancement and noise reduction features. This paper presents a segmentation algorithm that extracts uniform text and other uniform color objects that carry detail information. The algorithm consists of four steps. First the test and objects are extracted from the image. Next, they are tested for color constancy and other features to decide if they should be represented by the MRC foreground layers. The objects that are chosen are then clustered in color space. The image is finally segmented such that each foreground layer codes the objects from the same color cluster.

Paper Details

Date Published: 17 January 2005
PDF: 12 pages
Proc. SPIE 5667, Color Imaging X: Processing, Hardcopy, and Applications, (17 January 2005); doi: 10.1117/12.588317
Show Author Affiliations
Zhigang Fan, Xerox Corp. (United States)
Timothy Jacobs, Xerox Corp. (United States)


Published in SPIE Proceedings Vol. 5667:
Color Imaging X: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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