Simplified segmentation for compound image compression

There are three basic segmentation schemes for compound image compression: object-based, layer-based, and block-based. This paper discusses the relative advantages of each scheme and architecture, and studies the use of fast classification techniques for a segmentation that can be used together with a chosen compression architecture. Particularly, we consider classification techniques working on approximate object boundaries, which reaches the localization and precision of the segmentation, but in exchange allows faster, one-pass segmentation, low memory requirements, and segmentation map that is better matched to existing compression methods. We show numerical results obtained on a printer application environment, where rigorous standards of visual quality have to be satisfied