filters.dbscan

The DBSCAN filter performs Density-Based Spatial Clustering of Applications with Noise (DBSCAN) [Ester1996] and labels each point with its associated cluster ID. Points that do not belong to a cluster are given a Cluster ID of -1. The remaining clusters are labeled as integers starting from 0.

Default Embedded Stage

This stage is enabled by default

New in version 2.1.

Example

[
    "input.las",
    {
        "type":"filters.dbscan",
        "min_points":10,
        "eps":2.0,
        "dimensions":"X,Y,Z"
    },
    {
        "type":"writers.bpf",
        "filename":"output.bpf",
        "output_dims":"X,Y,Z,ClusterID"
    }
]

Options

min_points

The minimum cluster size min_points should be greater than or equal to the number of dimensions (e.g., X, Y, and Z) plus one. As a rule of thumb, two times the number of dimensions is often used. [Default: 6]

eps

The epsilon parameter can be estimated from a k-distance graph (for k = min_points minus one). eps defines the Euclidean distance that will be used when searching for neighbors. [Default: 1.0]

dimensions

Comma-separated string indicating dimensions to use for clustering. [Default: X,Y,Z]