Characterization of opponent channels, automated detection of PQ defects, and green -noise mask design by dual-metric

Bong-Sun Lee, Purdue University

Abstract

In this document, we describe three different research topics: characterization of red-green and blue-yellow opponent channels, autonomous print quality (PQ) defect diagnosis, and design of stochastic green-noise masks using dual-metric (DBS and a measure of compactness). ^ For the first work of research, we explore a method to characterize opponent channel in human visual system. Responses of opponent-channels have been modeled in the past as a linear transformation of cone absorption values L, M, S. We asked two related questions: (i) which of these transformations is psychologically most plausible; (ii) is a linear transformation the right model, in the first place. We tested positions of pure colors for seven subjects in a xy chromaticity diagram as well as in a Boynton-MacLeod chromaticity diagram in log-coordinates. The results showed that neither of the two opponent channels can be adequately approximated by a single straight line. The red-green channel can be approximated by two straight lines. The blue-yellow channel can be approximated by a quadratic function, whose middle section coincides closely with the daylight locus. These results represent a violation of the necessary condition for any linear model to be an adequate description of opponent channels. We further show that the properties of the red-green channel (blue-yellow equilibrium line) measured in our experiment correspond to the properties of parvocellular-pathway cells in the visual system. Our further analysis showed that there was a correlation between the red and the green directions.^ The goal of the second project is to develop an image analysis tool to automatically identify LJ 9500 PQ defects from scans of the printed PQ test pages. We perform the detection algorithm which correctly identify each type of defect in the presence of a wide range of variation in the actual appearance of each type of defect. ^ In the third project, we propose a new approach to digital halftoning that generates stochastic dispersed-dot patterns in highlight/shadow textures and aperiodic clustered-dot patterns in midtone textures using dual-metric. ^

Degree

Ph.D.

Advisors

Jan P. Allebach, Purdue University, Zygmunt Pizlo, Purdue University.

Subject Area

Engineering, Electronics and Electrical

COinS