A comprehensive study of clustering a class of 2D shapes

TL;DR

This paper introduces new similarity measures for clustering 2D shapes based on archaeological pottery, combining Procrustes analysis and Dynamic Time Warping, to improve shape and size-based classification.

Contribution

It proposes novel similarity measures that integrate Procrustes analysis and Dynamic Time Warping for clustering 2D contours of archaeological artifacts.

Findings

Effective clustering of archaeological pottery shapes.

Improved shape and size discrimination in clustering.

Validation through computational experiments.

Abstract

The paper concerns clustering with respect to the shape and size of 2D contours that are boundaries of cross-sections of 3D objects of revolution. We propose a number of similarity measures based on combined disparate Procrustes analysis (PA) and Dynamic Time Warping (DTW) distances. Motivation and the main application for this study comes from archaeology. The performed computational experiments refer to the clustering of archaeological pottery.