https://github.com/mapbox/concaveman

A very fast 2D concave hull algorithm in JavaScript
https://github.com/mapbox/concaveman

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A very fast 2D concave hull algorithm in JavaScript

• Host: GitHub
• URL: https://github.com/mapbox/concaveman
• Owner: mapbox
• License: isc
• Created: 2016-02-10T11:30:34.000Z (about 10 years ago)
• Default Branch: master
• Last Pushed: 2025-07-16T14:28:54.000Z (8 months ago)
• Last Synced: 2026-01-05T01:43:24.906Z (about 2 months ago)
• Language: JavaScript
• Homepage:
• Size: 87.9 KB
• Stars: 719
• Watchers: 126
• Forks: 84
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
## concaveman

A very fast **2D concave hull** algorithm in JavaScript (generates a general outline of a point set).

[![Build Status](https://travis-ci.org/mapbox/concaveman.svg?branch=master)](https://travis-ci.org/mapbox/concaveman)

[![Coverage Status](https://coveralls.io/repos/github/mapbox/concaveman/badge.svg?branch=master)](https://coveralls.io/github/mapbox/concaveman?branch=master)

[![](https://img.shields.io/badge/simply-awesome-brightgreen.svg)](https://github.com/mourner/projects)



### Usage

```js

import concaveman from 'concaveman';

const points = [[10, 20], [30, 12.5], ...];

const polygon = concaveman(points);

```

Signature: `concaveman(points[, concavity = 2, lengthThreshold = 0])`

- `points` is an array of `[x, y]` points.

- `concavity` is a relative measure of concavity. `1` results in a relatively detailed shape, `Infinity` results in a convex hull.

You can use values lower than `1`, but they can produce pretty crazy shapes.

- `lengthThreshold`: when a segment length is under this threshold, it stops being considered for further detalization.

Higher values result in simpler shapes.

### Algorithm

The algorithm is based on ideas from the paper [A New Concave Hull Algorithm and Concaveness Measure

for n-dimensional Datasets, 2012](https://jise.iis.sinica.edu.tw/JISESearch/fullText?pId=245&code=5A9B97538372AA1)

by Jin-Seo Park and Se-Jong Oh.

This implementation dramatically improves performance over the one stated in the paper

(`O(rn)`, where `r` is a number of output points, to `O(n log n)`)

by introducing a fast _k nearest points to a segment_ algorithm,

a modification of a depth-first kNN R-tree search using a priority queue.

### TypeScript

[TypeScript type definitions](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/master/types/concaveman)

are available through `npm install --save @types/concaveman`.

### Dependencies

- [rbush](https://github.com/mourner/rbush) for point indexing

- [tinyqueue](https://github.com/mourner/tinyqueue) as a priority queue

- [point-in-polygon](https://github.com/substack/point-in-polygon) for point in polygon queries

- [robust-predicates](https://github.com/mourner/robust-predicates) for 3-point orientation tests

### C++ Port

In 2019, a [C++ port](https://github.com/sadaszewski/concaveman-cpp) has been created, allowing for efficient usage from C/C++, Python (via cffi) and other languages featuring an FFI and/or plug-in mechanism for C (e.g. a MATLAB MEX file should be easy to prepare).