PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractMultispectral imaging is an important tool in art conservation because it allows researchers to view under-drawing and restoration efforts on a painting. It is necessary to precisely align various images of the same painting using digital image processing techniques, however this is complicated by inconsistencies in image contents and the use of multiple cameras. This paper seeks to develop an effective method to automatically align and rescale multispectral images of paintings. Key point identification using the Speeded-Up Robust Feature detection algorithm with refinement by Random Sample Consensus fitting was determined to be an accurate and efficient method for aligning visible and infrared multispectral images.
Degree ProgramHonors College
Materials Science and Engineering