Segmentation for mixed raster contents with multiple extracted constant color areas

Zhigang Fan; Timothy Jacobs

doi:10.1117/12.588317

17 January 2005 Segmentation for mixed raster contents with multiple extracted constant color areas

Zhigang Fan, Timothy Jacobs

Proceedings Volume 5667, Color Imaging X: Processing, Hardcopy, and Applications; (2005) https://doi.org/10.1117/12.588317
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

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.

Citation Download Citation

Zhigang Fan and Timothy Jacobs "Segmentation for mixed raster contents with multiple extracted constant color areas", Proc. SPIE 5667, Color Imaging X: Processing, Hardcopy, and Applications, (17 January 2005); https://doi.org/10.1117/12.588317

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