# Projective Geometry/Classic/Projective Transformations/Transformations of the projective line

< Projective Geometry | Classic/Projective TransformationsLet *X* be a point on the *x*-axis. A projective transformation can be defined geometrically for this line by picking a pair of points *P*, *Q*, and a line *m*, all within the same *x-y* plane which contains the *x*-axis upon which the transformation will be performed.

Points *P* and *Q* represent two different observers, or points of view. Point *R* is the position of some object they are observing. Line *m* is the objective world which they are observing, and the *x*-axis is the subjective perception of *m*.

Draw line *l* through points *P* and *X*. Line *l* crosses line *m* at point *R*. Then draw line *t* through points *Q* and *R*: line *t* will cross the *x*-axis at point *T*. Point *T* is the transform of point *X* [Paiva].

## Contents

## AnalysisEdit

The above is a synthetic description of a one-dimensional projective transformation. It is now desired to convert it to an analytical (Cartesian) description.

Let point *X* have coordinates *(x _{0},0)*. Let point

*P*have coordinates . Let point

*Q*have coordinates . Let line

*m*have slope

*m*(

*m*is being overloaded in meaning).

The slope of line *l* is

so an arbitrary point *(x,y)* on line *l* is given by the equation

- ,

On the other hand, any point *(x,y)* on line *m* is described by

The intersection of lines *l* and *m* is point *R*, and it is obtained by combining equations (1) and (2):

Joining the *x* terms yields

and solving for *x* we obtain

*x*_{1} is the abscissa of *R*. The ordinate of *R* is

Now, knowing both *Q* and *R*, the slope of line *n* is

We want to find the intersection of line *n* and the *x*-axis, so let

The value of *λ* must be adjusted so that both sides of vector equation (3) are equal. Equation (3) is actually two equations, one for abscissas and one for ordinates. The one for ordinates is

Solve for lambda,

The equation for abscissas is

which together with equation (4) yields

which is the abscissa of *T*.

Substitute the values of *x _{1}* and

*y*into equation (5),

_{1}Dissolve the fractions in both numerator and denominator:

Simplify and relabel *x* as *t(x)*:

*t(x)* is the projective transformation.

Transformation *t*(*x*) can be simplified further. First, add its two terms to form a fraction:

Then, define the coefficients *α*, *β*, *γ* and *δ* to be the following

Substitute these coefficients into equation (6), in order to produce

This is the Möbius transformation or linear fractional transformation.

## Inverse transformationEdit

It is clear from the synthetic definition that the inverse transformation is obtained by exchanging points *P* and *Q*. This can also be shown analytically. If *P* ↔ *Q*, then *α* → *α′*, *β* → *β′*, *γ* → *γ′*, and *δ* → *δ′*, where

Therefore if the forwards transformation is

then the transformation *t′* obtained by exchanging *P* and *Q* (*P* ↔ *Q*) is:

Then

- .

Dissolve the fractions in both numerator and denominator of the right side of this last equation:

- .

Therefore *t*′(*x*) = *t*^{−1}(*x*): the inverse projective transformation is obtained by exchanging observers *P* and *Q*, or by letting α ↔ δ, β → −β, and γ → −γ. This is, by the way, analogous to the procedure for obtaining the inverse of a two-dimensional matrix:

where Δ = α δ − β γ is the determinant.

## Identity transformationEdit

Also analogous with matrices is the identity transformation, which is obtained by letting α = 1, β = 0, γ = 0, and δ = 1, so that

## Composition of transformationsEdit

It remains to show that there is closure in the composition of transformations. One transformation operating on another transformation produces a third transformation. Let the first transformation be *t*_{1} and the second one be *t*_{2}:

The composition of these two transformations is

Define the coefficients α_{3}, β_{3}, γ_{3} and δ_{3} to be equal to

Substitute these coefficients into to obtain

Projections operate in a way analogous to matrices. In fact, the composition of transformations can be obtained by multiplying matrices:

Since matrices multiply associatively, it follows that composition of projections is also associative.

Projections have: an operation (composition), associativity, an identity, an inverse and closure, so they form a group.

## The cross-ratio defined by means of a projectionEdit

Let there be a transformation *t _{s}* such that

*t*(

_{s}*A*) = ,

*t*(

_{s}*B*) = 0,

*t*(

_{s}*C*) = 1. Then the value of

*t*(

_{s}*D*) is called the cross-ratio of points

*A*,

*B*,

*C*and

*D*, and is denoted as [

*A*,

*B*,

*C*,

*D*]

_{s}:

Let

then the three conditions for *t _{s}(x)* are met when

Equation (7) implies that , therefore . Equation (8) implies that , so that . Equation (9) becomes

which implies

Therefore

In equation (10), it is seen that *t _{s}*(

*D*) does not depend on the coefficients of the projection

*t*. It only depends on the positions of the points on the "subjective" projective line. This means that the cross-ratio depends only on the relative distances among four collinear points, and not on the projective transformation which was used to obtain (or define) the cross-ratio. The cross ratio is therefore

_{s}## Conservation of cross-ratioEdit

Transformations on the projective line preserve cross ratio. This will now be proven. Let there be four (collinear) points *A*, *B*, *C*, *D*. Their cross-ratio is given by equation (11). Let *S(x)* be a projective transformation:

where . Then

Therefore [S(A) S(B) S(C) S(D)] = [A B C D], Q.E.D.