Semilandmarks: a method for quantifying curves and surfaces

TLDR

Geometric morphometrics analyzes landmark coordinates, but many structures cannot be quantified with traditional landmarks, and semilandmarks enable quantification of 2‑ or 3‑D curves and surfaces alongside traditional landmarks. The study introduces sliding semilandmarks, discusses their applications and limitations, and demonstrates how the algorithm can estimate missing data in incomplete specimens. We present a sliding semilandmark algorithm that quantifies 2‑/3‑D curves and surfaces, discusses its applications and limitations, and applies it to estimate missing data in incomplete specimens. Download the complete Yellow Book on Virtual Morphology and Evolutionary Morphometrics in the new millennium.

Abstract

Quantitative shape analysis using geometric morphometrics is based on the statistical analysis of landmark coordinates. Many structures, however, cannot be quantified using traditional landmarks. Semilandmarks make it possible to quantify two or three-dimensional homologous curves and sur- faces, and analyse them together with traditional landmarks. Here we first introduce the concept of sliding semilandmarks and discuss applications and limitations of this method. In a second part we show how the sliding semilandmark algorithm can be used to estimate missing data in incomplete specimens. Download the complete Yellow Book on Virtual Morphology and Evolutionary Morphometrics in the new millenium.