# Convex and concave polygons

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An example of a convex polygon: a regular pentagon

In geometry, a polygon can be either convex or concave (non-convex or reentrant).

## Convex polygons

A convex polygon is a simple polygon whose interior is a convex set.[1] In a convex polygon, all interior angles are less than 180 degrees.

### Properties of convex polygons

The following properties of a simple polygon are all equivalent to convexity:

• Every internal angle is less than or equal to 180 degrees.
• Every line segment between two vertices remains inside or on the boundary of the polygon.
• The polygon is entirely contained in a closed half-plane defined by each of its edges.
• For each edge, the vertices not contained in the edge are on the same side of the line that the edge defines.
• The angle at each vertex contains all other vertices in its interior (except the three vertices defining the angle).

Additional properties of convex polygons:

• The intersection of two convex polygons is a convex polygon.
• Helly's theorem: For every collection of at least 3 convex polygons: if the intersection of every 3 of them is nonempty, then the whole collection has a nonempty intersection.
• Krein–Milman theorem: A convex polygon is the convex hull of its vertices. I.e.: it is fully defined by the set of its vertices. I.e.: one only needs the corners of the polygon to recover the entire polygon shape.
• Hyperplane separation theorem: Any two convex polygons have a separator line. If the polygons are closed and at least one of them is compact, then there are even two parallel separator lines (with a gap between them).
• Inscribed triangle property: Of all triangles contained in a convex polygon, there exists a triangle with a maximal area whose vertices are all polygon vertices.[2]
• Inscribing triangle property: every convex polygon with area A can be inscribed in a triangle of area at most equal to 2A. Equality holds (exclusively) for a parallelogram.[3]
• The Mean width of a convex polygon is equal to its perimeter divided by pi. So its width is the diameter of a circle with the same perimeter as the polygon.[4]

Every polygon circumscribed in a circle (such that all vertices of the polygon touch the circumference of the circle) is convex.[5] However, not every convex polygon can be circumscribed in a circle.

### Strict convexity

A simple polygon is strictly convex if every internal angle is strictly less than 180 degrees. Equivalently, a polygon is strictly convex if every line segment between two nonadjacent vertices of the polygon is strictly interior to the polygon except at its endpoints.

Every nondegenerate triangle is strictly convex.

## Concave or non-convex polygons

An example of a concave polygon.

A simple polygon that is not convex is called concave,[6] non-convex[7] or reentrant.[8] A concave polygon will always have an interior angle with a measure that is greater than 180 degrees.[9]

It is always possible to partition a concave polygon into a set of convex polygons. A polynomial-time algorithm for finding a decomposition into as few convex polygons as possible is described by Chazelle & Dobkin (1985).[10]

## References

1. ^ Definition and properties of convex polygons with interactive animation.
2. ^ "Is the area of intersection of convex polygons always convex?". Math Stack Exchange.
3. ^ Weisstein, Eric W. "Triangle Circumscribing". Wolfram Math World.
4. ^ Jim Belk. "What's the average width of a convex polygon?". Math Stack Exchange.
5. ^ Lee, Jack. "Proof that every polygon with an inscribed circle is convex?". Math Stack Exchange.
6. ^ McConnell, Jeffrey J. (2006), Computer Graphics: Theory Into Practice, p. 130, ISBN 0-7637-2250-2.
7. ^ Leff, Lawrence (2008), Let's Review: Geometry, Hauppauge, NY: Barron's Educational Series, p. 66, ISBN 978-0-7641-4069-3
8. ^ Mason, J.I. (1946), "On the angles of a polygon", The Mathematical Gazette (The Mathematical Association) 30 (291): 237–238, JSTOR 3611229.
9. ^ Definition and properties of concave polygons with interactive animation.
10. ^ Chazelle, Bernard; Dobkin, David P. (1985), "Optimal convex decompositions", in Toussaint, G.T., Computational Geometry, Elsevier, pp. 63–133.