Whole-painting canvas analysis using high- and low-level features

Weave analysis of artist canvas examines x-ray images taken of the paintings. Algorithms assume an underlying regularity of the canvas weave over short distances and exploits short-space spectral analysis to determine the fundamental frequency of the horizontal and vertical thread regularity. However, many paintings are too large to be covered by a single x-ray. Feature point analysis exploits brushstrokes and composition to merge several x-ray images into a single one, taking into account and removing both spatial and amplitude distortions. Certain master artists used low-quality canvas that is more irregular than the norm. A theoretical study of quasi-periodic signals shows that while the expected spectrum is a peak that broadens as period irregularity increases, sample function spectra have distinct peaks having an envelope equal to the expected spectrum.