WikiMili The Free Encyclopedia

This article needs additional citations for verification .(April 2008) (Learn how and when to remove this template message) |

In Euclidean geometry, **uniform scaling** (or ** isotropic scaling**^{ [1] }) is a linear transformation that enlarges (increases) or shrinks (diminishes) objects by a scale factor that is the same in all directions. The result of uniform scaling is similar (in the geometric sense) to the original. A scale factor of 1 is normally allowed, so that congruent shapes are also classed as similar. Uniform scaling happens, for example, when enlarging or reducing a photograph, or when creating a scale model of a building, car, airplane, etc.

**Euclidean geometry** is a mathematical system attributed to Alexandrian Greek mathematician Euclid, which he described in his textbook on geometry: the *Elements*. Euclid's method consists in assuming a small set of intuitively appealing axioms, and deducing many other propositions (theorems) from these. Although many of Euclid's results had been stated by earlier mathematicians, Euclid was the first to show how these propositions could fit into a comprehensive deductive and logical system. The *Elements* begins with plane geometry, still taught in secondary school as the first axiomatic system and the first examples of formal proof. It goes on to the solid geometry of three dimensions. Much of the *Elements* states results of what are now called algebra and number theory, explained in geometrical language.

A **scale factor** is a number which scales, or multiplies, some quantity. In the equation *y* = *Cx*, *C* is the scale factor for *x*. *C* is also the coefficient of *x*, and may be called the constant of proportionality of *y* to *x*. For example, doubling distances corresponds to a scale factor of two for distance, while cutting a cake in half results in pieces with a scale factor for volume of one half. The basic equation for it is image over preimage.

Two geometrical objects are called **similar** if they both have the same shape, or one has the same shape as the mirror image of the other. More precisely, one can be obtained from the other by uniformly scaling, possibly with additional translation, rotation and reflection. This means that either object can be rescaled, repositioned, and reflected, so as to coincide precisely with the other object. If two objects are similar, each is congruent to the result of a particular uniform scaling of the other. A modern and novel perspective of similarity is to consider geometrical objects similar if one appears congruent to the other when zoomed in or out at some level.

- Matrix representation
- Scaling in arbitrary dimensions
- Using homogeneous coordinates
- Function dilation and contraction
- Particular cases
- Footnotes
- See also
- External links

More general is **scaling** with a separate scale factor for each axis direction. **Non-uniform scaling** (** anisotropic scaling**) is obtained when at least one of the scaling factors is different from the others; a special case is **directional scaling** or **stretching** (in one direction). Non-uniform scaling changes the shape of the object; e.g. a square may change into a rectangle, or into a parallelogram if the sides of the square are not parallel to the scaling axes (the angles between lines parallel to the axes are preserved, but not all angles). It occurs, for example, when a faraway billboard is viewed from an oblique angle, or when the shadow of a flat object falls on a surface that is not parallel to it.

A **shape** is the form of an object or its external boundary, outline, or external surface, as opposed to other properties such as color, texture or material composition.

When the scale factor is larger than 1, (uniform or non-uniform) scaling is sometimes also called **dilation** or **enlargement**. When the scale factor is a positive number smaller than 1, scaling is sometimes also called **contraction**.

In the most general sense, a scaling includes the case in which the directions of scaling are not perpendicular. It also includes the case in which one or more scale factors are equal to zero (projection), and the case of one or more negative scale factors (a directional scaling by -1 is equivalent to a reflection).

In linear algebra and functional analysis, a **projection** is a linear transformation from a vector space to itself such that . That is, whenever is applied twice to any value, it gives the same result as if it were applied once (idempotent). It leaves its image unchanged. Though abstract, this definition of "projection" formalizes and generalizes the idea of graphical projection. One can also consider the effect of a projection on a geometrical object by examining the effect of the projection on points in the object.

In mathematics, a **reflection** is a mapping from a Euclidean space to itself that is an isometry with a hyperplane as a set of fixed points; this set is called the axis or plane of reflection. The image of a figure by a reflection is its mirror image in the axis or plane of reflection. For example the mirror image of the small Latin letter **p** for a reflection with respect to a vertical axis would look like **q**. Its image by reflection in a horizontal axis would look like **b**. A reflection is an involution: when applied twice in succession, every point returns to its original location, and every geometrical object is restored to its original state.

Scaling is a linear transformation, and a special case of homothetic transformation. In most cases, the homothetic transformations are non-linear transformations.

In mathematics, a **homothety** is a transformation of an affine space determined by a point *S* called its *center* and a nonzero number *λ* called its *ratio*, which sends

A scaling can be represented by a scaling matrix. To scale an object by a vector *v* = (*v _{x}, v_{y}, v_{z}*), each point

As shown below, the multiplication will give the expected result:

Such a scaling changes the diameter of an object by a factor between the scale factors, the area by a factor between the smallest and the largest product of two scale factors, and the volume by the product of all three.

In geometry, a **diameter** of a circle is any straight line segment that passes through the center of the circle and whose endpoints lie on the circle. It can also be defined as the longest chord of the circle. Both definitions are also valid for the diameter of a sphere.

There are several well-known formulas for the areas of simple shapes such as triangles, rectangles, and circles. Using these formulas, the area of any polygon can be found by dividing the polygon into triangles. For shapes with curved boundary, calculus is usually required to compute the area. Indeed, the problem of determining the area of plane figures was a major motivation for the historical development of calculus.

**Volume** is the quantity of three-dimensional space enclosed by a closed surface, for example, the space that a substance or shape occupies or contains. Volume is often quantified numerically using the SI derived unit, the cubic metre. The volume of a container is generally understood to be the capacity of the container; i. e., the amount of fluid that the container could hold, rather than the amount of space the container itself displaces. Three dimensional mathematical shapes are also assigned volumes. Volumes of some simple shapes, such as regular, straight-edged, and circular shapes can be easily calculated using arithmetic formulas. Volumes of complicated shapes can be calculated with integral calculus if a formula exists for the shape's boundary. One-dimensional figures and two-dimensional shapes are assigned zero volume in the three-dimensional space.

The scaling is uniform if and only if the scaling factors are equal (*v _{x} = v_{y} = v_{z}*). If all except one of the scale factors are equal to 1, we have directional scaling.

In the case where *v _{x} = v_{y} = v_{z} = k*, scaling increases the area of any surface by a factor of k

In -dimensional space , uniform scaling by a factor is accomplished by scalar multiplication with , that is, multiplying each coordinate of each point by . As a special case of linear transformation, it can be achieved also by multiplying each point (viewed as a column vector) with a diagonal matrix whose entries on the diagonal are all equal to , namely .

Non-uniform scaling is accomplished by multiplication with any symmetric matrix. The eigenvalues of the matrix are the scale factors, and the corresponding eigenvectors are the axes along which each scale factor applies. A special case is a diagonal matrix, with arbitrary numbers along the diagonal: the axes of scaling are then the coordinate axes, and the transformation scales along each axis by the factor

In uniform scaling with a non-zero scale factor, all non-zero vectors retain their direction (as seen from the origin), or all have the direction reversed, depending on the sign of the scaling factor. In non-uniform scaling only the vectors that belong to an eigenspace will retain their direction. A vector that is the sum of two or more non-zero vectors belonging to different eigenspaces will be tilted towards the eigenspace with largest eigenvalue.

In projective geometry, often used in computer graphics, points are represented using homogeneous coordinates. To scale an object by a vector *v* = (*v _{x}, v_{y}, v_{z}*), each homogeneous coordinate vector

As shown below, the multiplication will give the expected result:

Since the last component of a homogeneous coordinate can be viewed as the denominator of the other three components, a uniform scaling by a common factor *s* (uniform scaling) can be accomplished by using this scaling matrix:

For each vector *p* = (*p _{x}, p_{y}, p_{z}*, 1) we would have

which would be equivalent to

Given a point , the dilation associates it with the point through the equations for

Therefore, given a function , the equation of the dilated function is

If , the transformation is horizontal; when , it is a dilation, when , it is a contraction.

If , the transformation is vertical; when it is a dilation, when , it is a contraction.

- ↑ Durand; Cutler. "Transformations" (PowerPoint). Massachusetts Institute of Technology. Retrieved 12 September 2008.

Wikimedia Commons has media related to . Scaling (geometry) |

- Understanding 2D Scaling and Understanding 3D Scaling by Roger Germundsson, The Wolfram Demonstrations Project.

**2D computer graphics** is the computer-based generation of digital images—mostly from two-dimensional models and by techniques specific to them.The word may stand for the branch of computer science that comprises such techniques or for the models themselves.

In geometry, an **affine transformation**, **affine map** or an **affinity** is a function between affine spaces which preserves points, straight lines and planes. Also, sets of parallel lines remain parallel after an affine transformation. An affine transformation does not necessarily preserve angles between lines or distances between points, though it does preserve ratios of distances between points lying on a straight line.

**Kinematics** is a branch of classical mechanics that describes the motion of points, bodies (objects), and systems of bodies without considering the forces that caused the motion. Kinematics, as a field of study, is often referred to as the "geometry of motion" and is occasionally seen as a branch of mathematics. A kinematics problem begins by describing the geometry of the system and declaring the initial conditions of any known values of position, velocity and/or acceleration of points within the system. Then, using arguments from geometry, the position, velocity and acceleration of any unknown parts of the system can be determined. The study of how forces act on bodies falls within kinetics, not kinematics. For further details, see analytical dynamics.

In linear algebra, the **column space** of a matrix *A* is the span of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation.

An orthogonal matrix is a square matrix whose columns and rows are orthogonal unit vectors, i.e.

In vector calculus, the **Jacobian matrix** is the matrix of all first-order partial derivatives of a vector-valued function. When the matrix is a square matrix, both the matrix and its determinant are referred to as the **Jacobian** in literature.

**Orthographic projection** is a means of representing three-dimensional objects in two dimensions. It is a form of parallel projection, in which all the projection lines are orthogonal to the projection plane, resulting in every plane of the scene appearing in affine transformation on the viewing surface. The obverse of an orthographic projection is an oblique projection, which is a parallel projection in which the projection lines are *not* orthogonal to the projection plane.

In Euclidean geometry, a **translation** is a geometric transformation that moves every point of a figure or a space by the same distance in a given direction.

In linear algebra, linear transformations can be represented by matrices. If is a linear transformation mapping to and is a column vector with entries, then

In linear algebra, a **rotation matrix** is a matrix that is used to perform a rotation in Euclidean space. For example, using the convention below, the matrix

In physics, the **Thomas precession**, named after Llewellyn Thomas, is a relativistic correction that applies to the spin of an elementary particle or the rotation of a macroscopic gyroscope and relates the angular velocity of the spin of a particle following a curvilinear orbit to the angular velocity of the orbital motion.

In linear algebra, an **eigenvector** or **characteristic vector** of a linear transformation is a non-zero vector that changes by only a scalar factor when that linear transformation is applied to it. More formally, if T is a linear transformation from a vector space V over a field F into itself and **v** is a vector in V that is not the zero vector, then **v** is an eigenvector of T if *T*(**v**) is a scalar multiple of **v**. This condition can be written as the equation

In mathematics, **Arnold's cat map** is a chaotic map from the torus into itself, named after Vladimir Arnold, who demonstrated its effects in the 1960s using an image of a cat, hence the name.

In geometry, a **point reflection** or **inversion in a point** is a type of isometry of Euclidean space. An object that is invariant under a point reflection is said to possess **point symmetry**; if it is invariant under point reflection through its center, it is said to possess **central symmetry** or to be **centrally symmetric.**

In linear algebra, **eigendecomposition** or sometimes **spectral decomposition** is the factorization of a matrix into a canonical form, whereby the matrix is represented in terms of its eigenvalues and eigenvectors. Only diagonalizable matrices can be factorized in this way.

The **Helmert transformation** is a transformation method within a three-dimensional space. It is frequently used in geodesy to produce distortion-free transformations from one datum to another. The Helmert transformation is also called a **seven-parameter transformation** and is a similarity transformation.

The **direct-quadrature-zero****transformation** or **zero-direct-quadrature****transformation** is a tensor that rotates the reference frame of a three-element vector or a three-by-three element matrix in an effort to simplify analysis. The DQZ transform is the product of the Clarke transform and the Park transform, first proposed in 1929 by Robert H. Park.

There are many ways to derive the Lorentz transformations utilizing a variety of physical principles, ranging from Maxwell's equations to Einstein's postulates of special relativity, and mathematical tools, spanning from elementary algebra and hyperbolic functions, to linear algebra and group theory.

This page is based on this Wikipedia article

Text is available under the CC BY-SA 4.0 license; additional terms may apply.

Images, videos and audio are available under their respective licenses.

Text is available under the CC BY-SA 4.0 license; additional terms may apply.

Images, videos and audio are available under their respective licenses.