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Hausdorff distance

Hausdorff distance is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Hausdorff distance rather than just read about it. In short: In mathematics, the Hausdorff distance, or Hausdorff metric, also called Pompeiu–Hausdorff distance, measures how far two subsets of a metric space are from each other. It turns the set of non-empty compact subsets of a metric space into a metric space in its own right.

Hausdorff distance — main illustration
Hausdorff distance — illustration

Key takeaways

  • Hausdorff distance belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Hausdorff distance to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Hausdorff distance from memory before moving on to harder problems.

Reference excerpt

In mathematics, the Hausdorff distance, or Hausdorff metric, also called Pompeiu–Hausdorff distance, measures how far two subsets of a metric space are from each other. It turns the set of non-empty compact subsets of a metric space into a metric space in its own right. It is named after Felix Hausdorff and Dimitrie Pompeiu. Informally, two sets are close in the Hausdorff distance if every point of either set is close to some point of the other set. The Hausdorff distance is the longest distance someone can be forced to travel by an adversary who chooses a point in one of the two sets, from where they then must travel to the other set. In other words, it is the greatest of all the distances from a point in one set to the closest point in the other set. This distance was first introduced by Hausdorff in his book Grundzüge der Mengenlehre, first published in 1914, although a very close relative appeared in the doctoral thesis of Maurice Fréchet in 1906, in his study of the space of all continuous curves from [ 0 , 1 ] → R 3 {\displaystyle [0,1]\to \mathbb {R} ^{3}} .

Definition

Let ( M , d ) {\textstyle (M,d)} be a metric space. For each pair of non-empty subsets X ⊂ M {\textstyle X\subset M} and Y ⊂ M {\textstyle Y\subset M} , the Hausdorff distance between X {\textstyle X} and Y {\displaystyle Y} is defined as

d H ( X , Y ) := max { sup x ∈ X d ( x , Y ) , sup y ∈ Y d ( X , y ) } , {\displaystyle d_{\mathrm {H} }(X,Y):=\max \left\{\,\sup _{x\in X}d(x,Y),\ \sup _{y\in Y}d(X,y)\,\right\},}

where sup {\textstyle \operatorname {sup} } represents the supremum operator, d ( a , B ) := inf b ∈ B d ( a , b ) {\textstyle d(a,B):=\displaystyle \inf _{b\in B}d(a,b)} quantifies the distance from a point a ∈ X {\textstyle a\in X} to the subset B ⊆ X {\textstyle B\subseteq X} , and inf {\textstyle \operatorname {inf} } is the infimum operator. An equivalent definition is as follows. For each set X ⊂ M , {\displaystyle X\subset M,} let

X ε := ⋃ x ∈ X { z ∈ M ∣ d ( z , x ) < ε } , {\displaystyle X_{\varepsilon }:=\bigcup _{x\in X}\{z\in M\mid d(z,x)<\varepsilon \},}

which is the set of all points within ε {\textstyle \varepsilon } of the set X {\textstyle X} (sometimes called the ε {\textstyle \varepsilon } -fattening of X {\textstyle X} or a generalized ball of radius ε {\textstyle \varepsilon } around X {\textstyle X} ). Then, the Hausdorff distance between X {\textstyle X} and Y {\textstyle Y} is defined as

d H ( X , Y ) := inf { ε ≥ 0 ∣ X ⊆ Y ε and Y ⊆ X ε } . {\displaystyle d_{\mathrm {H} }(X,Y):=\inf\{\varepsilon \geq 0\mid X\subseteq Y_{\varepsilon }{\text{ and }}Y\subseteq X_{\varepsilon }\}.}

Equivalently,

… excerpt ends here. Continue reading the full article.

Illustrations

Hausdorff distance: Oceanic pole of inaccessibility at .mw-parser-output .geo-default,.mw-parser-output .geo-dms,.mw-parser-output .geo-dec{display:inline}.mw-parser-output .geo-nondefault,.mw-parser-output .geo-multi-punct,.mw-parser-output .geo-inline-hidden{display:none}.mw-parser-output .longitude,.mw-parser-output .latitude{white-space:nowrap}49°01′38″S 123°26′04″W / 49.0273°S 123.4345°W / -49.0273; -123.4345 (Oceanic Pole of Inaccessibility)
Oceanic pole of inaccessibility at .mw-parser-output .geo-default,.mw-parser-output .geo-dms,.mw-parser-output .geo-dec{display:inline}.mw-parser-output .geo-nondefault,.mw-parser-output .geo-multi-punct,.mw-parser-output .geo-inline-hidden{display:none}.mw-parser-output .longitude,.mw-parser-output .latitude{white-space:nowrap}49°01′38″S 123°26′04″W / 49.0273°S 123.4345°W / -49.0273; -123.4345 (Oceanic Pole of Inaccessibility)

Worked examples

Example 1 — a first encounter with Hausdorff distance

Start with the simplest possible case. Write down what Hausdorff distance claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Hausdorff distance before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Hausdorff distance ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Hausdorff distance

In research
Hausdorff distance appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Hausdorff distance in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Hausdorff distance is common in secondary-school and first-year university syllabi. It links to neighbouring topics Distance, Metric geometry, so understanding it makes those chapters shorter.
In everyday life
Look for Hausdorff distance outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Hausdorff distance in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Hausdorff distance means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Hausdorff distance out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Hausdorff distance in simple terms?

In mathematics, the Hausdorff distance, or Hausdorff metric, also called Pompeiu–Hausdorff distance, measures how far two subsets of a metric space are from each other. It turns the set of non-empty compact subsets of a metric space into a metric space in its own right.

Why does Hausdorff distance matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Hausdorff distance?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Hausdorff distance.

Tags

  • Distance
  • Metric geometry

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