A proof of concept for aligning sketches to their corresponding painting

Bachelor thesis (2022)

Authors

M.E. Radder Electrical Engineering, Mathematics and Computer Science

Contributors

R.T. Wiersma Computer Graphics and Visualisation - EEMCS (supervisor 1)
Ricardo Marroquim Computer Graphics and Visualisation - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Marit Radder
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Published Date

23-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Aligning sketches to their corresponding painting could give more insight into the creative process of an artist. This is a difficult task that cannot be solved directly with classical image registration techniques. Typically, features such as cracks and brushstrokes are used to match different modalities. A sketch does not contain such artifacts and is often roughly similar to the final painting. Therefore the following question rises what suitable feature detection, feature extraction/description, and transform model estimation methods can be used to align sketches to their corresponding painting. This paper provides a proof of concept by taking a manual feature detection, and a histogram of orientations as a feature description. We demonstrate that our algorithm can automatically align sketches with up to 1.4 percent of the accuracy of manual alignment.