Perceptual significance hierarchy: a computer vision theory for color separation

Authors:
Deborah Walters;Ganapathy Krishnan
Affiliations:
Computer Science Department, University at Buffalo, Buffalo, NY;Computer Science Department, University at Buffalo, Buffalo, NY
Venue:
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Year:
1987

Citing 3
Cited 0

Selection of image primitives for general-purpose visual processing

Computer Vision, Graphics, and Image Processing - Special issue on human and machine vission, part II
Tint fill

SIGGRAPH '79 Proceedings of the 6th annual conference on Computer graphics and interactive techniques
The viewer's place in theories of vision

IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

A Perceptual Significance Hierarchy (PSH) for line art images is developed which represents the relative perceptual significance of each image component. This is possible through the use of a set of image-features which are used by the human visual system. The PSH and related rho-space computer vIsion algorithms can be used to automate the fake color separation process used by the printing industry. This is accomplished by adding rudimentary visual processing capabilities to a computer graphics system.