Rochester Institute of Technology Rochester, New York COLLEGE of SCIENCE Chester F. Carlson Center for Imaging Science Color Modeling: 1050-813. 1051-776 1.0 Title: Color Modeling Date: May 6, 2004 Credit Hours: __4__ Prerequisite(s): Applied Colorimetry 1050-702 or 1051-775, Color Measurement Lab I and II 1050-721 and 1050-722 Course proposed by: Roy S. Berns 2.0 Course information: Contact hours Maximum students/section Classroom 3 20 Lab 3 20 Studio Other (specify _______) Quarter(s) offered (check) ____ Fall ____ Winter __X__ Spring _____ Summer Students required to take this course: Color Science MS, PhD Imaging Science MS, PhD, color-imaging track Students who might elect to take the course: Graduate students in printing 3.0 Goals of the course: To provide an in-depth knowledge of modeling techniques used in coloration systems. To gain experience using multivariate statistics and nonlinear optimization. To understand the trade-offs between analytical and empirical models. To improve technical writing skills.4.0 Course description 1050-813 Color Modeling This course explores mathematical techniques for predicting the spectral and colorimetric properties of colored materials and images from user-controlled drive signals. Color systems that are modeled include paint, computer-controlled LCD, continuous and halftone printing, and spectral cameras. Accompanying laboratory stresses the use of multivariate statistics, nonlinear optimization, and technical writing. Final laboratory consists of a spectral-based color reproduction system including input, display, and printed output. (1050-702) Class 3, Laboratory 3, Credit 4 (S) 5.0 Possible resources 5.1 Berns, R.S., Billmeyer and Saltzman’s Principles of Color Technology, 3rd Ed.; Wiley-Interscience: New York, (2000). 5.2 Assigned journal and proceedings papers. 6.0 Topics (outline): 6.1 A generic approach to color modeling. 6.2 Bouguer and Beer’s law. 6.3 Kubelka-Munk turbid media theory. 6.4 Spectral matching algorithms. 6.5 Colorimetric matching algorithms. 6.6 Use of Kubelka-Munk theory in the coloration of opaque paints. 6.7 Colorimetric characterization of CRT and LCD displays. 6.8 Principal component analysis. 6.9 Dye estimation of photographic materials using principal component analysis. 6.10 Spectral imaging. 6.11Spectral models of halftone printing using the Yule-Nielsen-Spectral-Neugebauer equation. 6.12End-to-end spectral color reproduction. 7.0 Intended learning outcomes and associated assessment methods of those outcomes Learning outcome Exams and quizzes Homework/Project assignments 7.1 Kubelka-Munk analysis of unknown paint mixtures X 7.2 Colorimetry of LCD displays X 7.3 Principal component Xanalysis of photographic materials 7.4 Spectral camera model using principal component analysis X 7.5 Spectral printer model using the Yule-Nielsen-Spectral-Neugebauer equation X 7.6 End-to-end spectral color reproduction X 8.0 Program or general education goals supported by this course 8.1 Enable students to obtain an understanding of the concepts of color modeling including the “generic approach.” (COS/Color Science) 8.2 Develop the ability to work with large datasets. (COS/Color Science) 8.3 Understand various models relating spectral and colorimetric data with input drive signals. (COS/Color Science) 8.4 Improve laboratory skills and technical writing. (COS/Color Science) 8.5 Apply concepts of multivariate statistics and nonlinear optimization to color modeling tasks. (COS/Color Science) 9.0 Other relevant information (such as special classroom, studio, or lab needs, special scheduling, media requirements, etc.) 9.1 Access to RIT Munsell Color Science Laboratory instrumentation and facilities required. 10.0 Supplemental information -