Leaf Clustering Using Circular Densities
Abstract
In the biology field of botany, leaf shape recognition is an important task. One way of characterising the leaf shape is through the centroid contour distances (CCD). Each CCD path might have different resolution, so normalisation is done by associating each contour to a circular density. Densities are rotated by subtracting the mean or mode preferred direction. Distance measures between densities are used to produce a hierarchical clustering method to cluster the leaves. We illustrate our approach with a motivating small dataset as well as a larger dataset.
Fields of Study & Subjects
Advanced Clustering Algorithms Research
Bayesian Methods and Mixture Models
Image Retrieval and Classification Techniques
Publication details
- Journal / source
- Model Assisted Statistics and Applications
- Volume
- 21
- Issue
- 1
- Pages
- 65–72
- Publication date
- 29 January 2026
- Language
- EN