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Bézier curve

From Wikipedia, the free encyclopedia

In the mathematical field of numerical analysis, a Bézier curve is a parametric curve important in computer graphics. Generalizations of Bézier curves to higher dimensions are called Bézier surfaces, of which the Bézier triangle is a special case.

Bézier curves were widely publicised in 1962 by the French engineer Pierre Bézier, who used them to design automobile bodies. The curves were first developed in 1959 by Paul de Casteljau using de Casteljau's algorithm, a numerically stable method to evaluate Bézier curves.

Contents

[edit] Examination of cases

[edit] Linear Bézier curves

Given points P0 and P1, a linear Bézier curve is just a straight line between those two points. The curve is given by

\mathbf{B}(t)=(1-t)\mathbf{P}_0 + t\mathbf{P}_1 \mbox{ , } t \in [0,1].

[edit] Quadratic Bézier curves

A quadratic Bézier curve is the path traced by the function B(t), given points P0, P1, and P2,

\mathbf{B}(t) = (1 - t)^{2}\mathbf{P}_0 + 2t(1 - t)\mathbf{P}_1 + t^{2}\mathbf{P}_2 \mbox{ , } t \in [0,1].

TrueType fonts use Bézier splines composed of the quadratic Bézier curves.

[edit] Cubic Bézier curves

Cubic Bézier curve
Enlarge
Cubic Bézier curve

Four points P0, P1, P2 and P3 in the plane or in three-dimensional space define a cubic Bézier curve. The curve starts at P0 going toward P1 and arrives at P3 coming from the direction of P2. Usually, it will not pass through P1 or P2; these points are only there to provide directional information. The distance between P0 and P1 determines "how long" the curve moves into direction P2 before turning towards P3.

The parametric form of the curve is:

\mathbf{B}(t)=\mathbf{P}_0(1-t)^3+3\mathbf{P}_1t(1-t)^2+3\mathbf{P}_2t^2(1-t)+\mathbf{P}_3t^3 \mbox{ , } t \in [0,1].

Modern imaging systems like PostScript, Asymptote and Metafont use Bézier splines composed of cubic Bézier curves for drawing curved shapes.

[edit] Generalization

The Bézier curve of degree n can be generalized as follows. Given points P0, P1,..., Pn, the Bézier curve is

\mathbf{B}(t)=\sum_{i=0}^n {n\choose i}\mathbf{P}_i(1-t)^{n-i}t^i =\mathbf{P}_0(1-t)^n+{n\choose 1}\mathbf{P}_1(1-t)^{n-1}t+\cdots+\mathbf{P}_nt^n \mbox{ , } t \in [0,1].

For example, for n = 5:

\mathbf{B}(t)=\mathbf{P}_0(1-t)^5+5\mathbf{P}_1t(1-t)^4+10\mathbf{P}_2t^2(1-t)^3+10\mathbf{P}_3t^3(1-t)^2+5\mathbf{P}_4t^4(1-t)+\mathbf{P}_5t^5 \mbox{ , } t \in [0,1].

This formula can be expressed recursively as follows: Let \mathbf{B}_{\mathbf{P}_0\mathbf{P}_1\ldots\mathbf{P}_n} denote the Bézier curve determined by the points P0, P1,..., Pn. Then

\mathbf{B}(t) = \mathbf{B}_{\mathbf{P}_0\mathbf{P}_1\ldots\mathbf{P}_n}(t) = (1-t)\mathbf{B}_{\mathbf{P}_0\mathbf{P}_1\ldots\mathbf{P}_{n-1}}(t) + t\mathbf{B}_{\mathbf{P}_1\mathbf{P}_2\ldots\mathbf{P}_n}(t)

In words, the degree n Bézier curve is an interpolation between two degree n − 1 Bézier curves.

[edit] Terminology

Some terminology is associated with these parametric curves. We have

\mathbf{B}(t) = \sum_{i=0}^n \mathbf{P}_i\mathbf{b}_{i,n}(t),\quad t\in[0,1]

where the polynomials

\mathbf{b}_{i,n}(t) = {n\choose i} t^i (1-t)^{n-i},\quad i=0,\ldots n

are known as Bernstein basis polynomials of degree n, defining 00 = 1.

The points Pi are called control points for the Bézier curve. The polygon formed by connecting the Bézier points with lines, starting with P0 and finishing with Pn, is called the Bézier polygon (or control polygon). The convex hull of the Bézier polygon contains the Bézier curve.

[edit] Notes

  • The curve begins at P0 and ends at Pn; this is the so-called endpoint interpolation property.
  • The curve is a straight line if and only if all the control points lie on the curve. Similarly, the Bézier curve is a straight line if and only if the control points are collinear.
  • The start (end) of the curve is tangent to the first (last) section of the Bézier polygon.
  • A curve can be split at any point into 2 subcurves, or into arbitrarily many subcurves, each of which is also a Bézier curve.
  • Some curves that seem simple, such as the circle, cannot be described exactly by a Bézier or piecewise Bézier curve (though a four-piece Bézier curve can approximate a circle, with a maximum radial error of less than one part in a thousand, when each inner control point is the distance (4/3) * (sqrt (2) - 1) horizontally or vertically from an outer control point on a unit circle).
  • The curve at a fixed offset from a given Bézier curve, often called an offset curve (lying "parallel" to the original curve, like the offset between rails in a railroad track), cannot be exactly formed by a Bézier curve (except in some trivial cases). However, there are heuristic methods that usually give an adequate approximation for practical purposes.

[edit] Constructing Bézier curves

[edit] Linear curves

The t in the function for a linear Bézier curve can be thought of as describing how far B(t) is from P0 to P1. For example when t=0.25, B(t) is one quarter of the way from point P0 to P1. As t varies from 0 to 1, B(t) describes a straight line from P0 to P1.

[edit] Quadratic curves

For quadratic Bézier curves one can construct intermediate points Q0 and Q1 such that as t varies from 0 to 1:

  • Point Q0 varies from P0 to P1 and describes a linear Bézier curve.
  • Point Q1 varies from P1 to P2 and describes a linear Bézier curve.
  • Point B(t) varies from Q0 to Q1 and describes a quadratic Bézier curve.
Construction of a quadratic Bézier curve
Construction of a quadratic Bézier curve
Animation t in [0,1]
Animation t in [0,1]


[edit] Higher order curves

For higher order curves one needs correspondingly more intermediate points. For cubic curves one can construct intermediate points Q0, Q1 & Q2 that describe linear Bézier curves, and points R0 & R1 that describe quadratic Bézier curves:

Construction of a cubic Bézier curve
Construction of a cubic Bézier curve
Animation t in [0,1]
Animation t in [0,1]


And for fourth order curves one can construct intermediate points Q0, Q1, Q2 & Q3 that describe linear Bézier curves, points R0, R1 & R2 that describe quadratic Bézier curves, and points S0 & S1 that describe cubic Bézier curves:

Construction of a 4th order Bézier curve
Construction of a 4th order Bézier curve
Animation t in [0,1]
Animation t in [0,1]


[edit] Application in computer graphics

Bézier path in Adobe Illustrator CS2
Enlarge
Bézier path in Adobe Illustrator CS2

Bézier curves are widely used in computer graphics to model smooth curves. As the curve is completely contained in the convex hull of its control points, the points can be graphically displayed and used to manipulate the curve intuitively. Affine transformations such as translation, scaling and rotation can be applied on the curve by applying the respective transform on the control points of the curve.

Quadratic and cubic Bézier curves are most common; higher degree curves are more expensive to evaluate. When more complex shapes are needed low order Bézier curves are patched together. To guarantee smoothness, the control point at which two curves meet and one control point on either side must be collinear. This is commonly referred to as a "path" in programs like Adobe Illustrator or Inkscape. These poly-Bézier curves can also be seen in the SVG file format.

The simplest method for scan converting a Bézier curve is to evaluate it at many closely spaced points and scan convert the approximating sequence of line segments. However, it does not guarantee that the rasterized output looks sufficiently smooth because the points may be spaced too far apart. Conversely it may generate too many points in areas where the curve is close to linear. A common adaptive method is recursive subdivision, in which a curve's control points are checked to see if the curve approximates a line segment to within a small tolerance. If not, the curve is subdivided parametrically into two segments, 0 \le t \le 0.5 and 0.5 \le t \le 1 and the same procedure applied to recursively to each half. There are also forward differencing methods, but great care must be taken to analyse error propagation. Analytical methods where a spline is intersected with each scan line involve finding roots of cubic polynomials (for cubic splines) and dealing with multiple roots, so they are not often used in practice.

[edit] Code example

The following code is a simple practical example showing how to plot a cubic Bezier curve in the C programming language. Note, this simply computes the coefficients of the polynomial and runs through a series of t values from 0 to 1 — in practice this is not how it is usually done - a recursive solution is often faster, taking fewer processor cycles at the expense of requiring more memory temporarily. However the direct method illustrated here is easier to understand and produces the same result. The following code has been factored to make its operation clear — an optimization in practice would be to compute the coefficients once and then re-use the result for the actual loop that computes the curve points — here they are recomputed every time, which is less efficient but helps to clarify the code.

The resulting curve can be plotted by drawing lines between successive points in the curve array — the more points, the smoother the curve.

On some architectures, the code below can also be optimized by dynamic programming. E.g. since dt is constant, cx * t changes a constant amount with every iteration. By repeatedly applying this optimization, the loop can be rewritten without any multiplications (though such a procedure is not numerically stable).

/*
Code to generate a cubic Bezier curve
*/

typedef struct
{
    float x;
    float y;
}
Point2D;

/*
cp is a 4 element array where:
cp[0] is the starting point, or P0 in the above diagram
cp[1] is the first control point, or P1 in the above diagram
cp[2] is the second control point, or P2 in the above diagram
cp[3] is the end point, or P3 in the above diagram
t is the parameter value, 0 <= t <= 1
*/

Point2D PointOnCubicBezier( Point2D* cp, float t )
{
    float   ax, bx, cx;
    float   ay, by, cy;
    float   tSquared, tCubed;
    Point2D result;

    /* calculate the polynomial coefficients */

    cx = 3.0 * (cp[1].x - cp[0].x);
    bx = 3.0 * (cp[2].x - cp[1].x) - cx;
    ax = cp[3].x - cp[0].x - cx - bx;
        
    cy = 3.0 * (cp[1].y - cp[0].y);
    by = 3.0 * (cp[2].y - cp[1].y) - cy;
    ay = cp[3].y - cp[0].y - cy - by;
        
    /* calculate the curve point at parameter value t */
        
    tSquared = t * t;
    tCubed = tSquared * t;
        
    result.x = (ax * tCubed) + (bx * tSquared) + (cx * t) + cp[0].x;
    result.y = (ay * tCubed) + (by * tSquared) + (cy * t) + cp[0].y;
        
    return result;
}

/*
 ComputeBezier fills an array of Point2D structs with the curve   
 points generated from the control points cp. Caller must 
 allocate sufficient memory for the result, which is 
 <sizeof(Point2D) numberOfPoints>
*/

void ComputeBezier( Point2D* cp, int numberOfPoints, Point2D* curve ) {
    float   dt;
    int   i;

    dt = 1.0 / ( numberOfPoints - 1 );

    for( i = 0; i < numberOfPoints; i++)
        curve[i] = PointOnCubicBezier( cp, i*dt );
}

Another application for Bézier curves is to describe paths for the motion of objects in animations, etc. Here, the x, y positions of the curve are not used to plot the curve but to position a graphic. When used in this fashion, the distance between successive points can become important, and in general these are not spaced equally — points will cluster more tightly where the control points are close to each other, and spread more widely for more distantly positioned control points. If linear motion speed is required, further processing is needed to spread the resulting points evenly along the desired path.

[edit] Rational Bézier curves

The rational Bézier adds adjustable weights to provide closer approximations to arbitrary shapes. The numerator is a weighted Bernstein-form Bézier curve and the denominator is a weighted sum of Bernstein polynomials.

Given n + 1 control points Pi, the rational Bézier curve can be described by:

\mathbf{B}(t) = \frac{ \sum_{i=0}^n b_{i,n}(t) \mathbf{P}_{i}w_i  } { \sum_{i=0}^n b_{i,n}(t) w_i  }

or simply

\mathbf{B}(t) = \frac{ \sum_{i=0}^n {n \choose i} t^i (1-t)^{n-i}\mathbf{P}_{i}w_i  } { \sum_{i=0}^n {n \choose i} t^i (1-t)^{n-i}w_i  }.

[edit] See also

[edit] References

[edit] External links

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