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A comparison of the QCPA framework to other existing pattern analyses and frameworks. For patternize see (Belleghem et al., 2017). For PAT-GEOM see Chan et al. (2018). For PAVO see Maia et al. (2013). For NaturePatternMatch see Stoddard et al. (2014). For Colourvision see Gawryszewski (2018). We would also like to point out approaches by Pike (2018) which operates on a similar principle to NaturePatternMatch and Weller & Westneat (2018) which shares similarities with PAVO.


Belleghem, S.M. Van, Papa, R., Ortiz-zuazaga, H., Hendrickx, F., Jiggins, C.D., Mcmillan, W.O., et al. 2017. Patternize : An R package for quantifying color pattern variation.

Chan, I.Z.W., Stevens, M. & Todd, P.A. 2018. PAT‐ GEOM: A Software Package for the Analysis of Animal Patterns. Methods Ecol. Evol. 2041–210X.13131.

Maia, R., Gruson, H., Endler, J.A. & White, T.E. 2018. pavo 2 . 0 : new tools for the spectral and spatial analysis of colour in R. bioRxiv, doi: 10.1101/427658.

Pike, T.W. 2018. Quantifying camouflage and conspicuousness using visual salience. Methods Ecol. Evol. 0–2.

Stoddard, M.C., Kilner, R.M. & Town, C. 2014. Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures. Nat. Commun. 5: 1–10. Nature Publishing Group.

Weller, H. & Westneat, M. 2018. Quantitative color profiling of digital images with earth mover’s distance using the R package colordistance. PeerJ Prepr. 1–31.

Comparative Overview
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