Abstract
The Studio for Scientific Imaging and Archiving of Cultural Heritage at RIT has built an imaging system capable of accurately measuring the spectral properties of artwork. To support this imaging system, complex software tools have been created that allow analysis and simulation with the data recorded by this imaging system, an obstacle to distributing data from this system to be analyzed by others. The arrival of a new color management standard, iccMAX, in 2018 has made sharing and using complex imaging data more practical. The standard supports spectral data and a flexible profile connection space that can represent many different color transforms, including customizable transforms through a programmable calculator tool. iccMAX would allow some of the processing used in the spectral imaging system for artwork to be embedded in an ICC color management profile. But the format does have limitations, and is lacking support for some mathematical tools used by the spectral imaging system. One toolset created in Matlab for the spectral imaging system enabled the extraction of paint concentration ratios from paintings, a practice called subtractive unmixing. This process relied on non-linear optimization routines and analysis of multiple pixels simultaneously, neither of which iccMAX supports. This work set out to find an effective method of using iccMAX to achieve a similar result to the Matlab unmixing process. As a part of this work, many modifications to existing unmixing algorithms were tested, and a linear algorithm was developed that is capable of identifying which paints were used in a mixture from a large set of possible options, and accurately estimating the concentrations of those paints at each location in a spectral image. The methodology used by this algorithm is quite simple in comparison to the previous unmixing workflow, but the two have similar accuracy and consistency, and most importantly the new algorithm can be implemented within an iccMAX profile.
Library of Congress Subject Headings
Art--Reproduction--Data processing; Spectrophotometry; Colorimetry; Image reconstruction
Publication Date
7-29-2021
Document Type
Thesis
Student Type
Graduate
Degree Name
Color Science (MS)
Advisor
Mark D. Fairchild
Advisor/Committee Member
Susan P. Farnand
Recommended Citation
Bodner, Benjamin, "Methods of Estimating Paint Concentrations from Spectral Images of Artwork for the iccMAX Framework" (2021). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/10875
Campus
RIT – Main Campus
Plan Codes
CLRS-MS