计算机图形学分形几何双语教学精选文档.ppt
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1、计算机图形学分形几何双语教学1本讲稿第一页,共四十六页Chapter 8 Fractal Geometry分形几何2本讲稿第二页,共四十六页8.1 what are fractalsv some pictures and animation films3本讲稿第三页,共四十六页vDefinitions of fractals 1.B.B.Mandelbrot(In 1982)A fractal is by definition a set for which the Hausdorff-Besicovitch dimension strictly exceeds the topological
2、 dimension.强调维数不是整数,是分数,又称分数维强调维数不是整数,是分数,又称分数维 4本讲稿第四页,共四十六页vKoch curve similarity dimension is 1.26 5本讲稿第五页,共四十六页6本讲稿第六页,共四十六页7本讲稿第七页,共四十六页vmiddle third Cantor set similarity dimension:0.68 8本讲稿第八页,共四十六页vSierpinski triangle similarity dimension:1.58 9本讲稿第九页,共四十六页10本讲稿第十页,共四十六页vDefinitions of fract
3、als 1.B.B.Mandelbrot(In 1982)A fractal is by definition a set for which the Hausdorff-Besicovitch dimension strictly exceeds the topological dimension.强调维数不是整数,是分数,又称分数维强调维数不是整数,是分数,又称分数维2.B.B.Mandelbrot(In 1986)A fractal is shape made of parts similar to the whole in some way.强调局部与整体自相似性强调局部与整体自相似性
4、11本讲稿第十一页,共四十六页peanon=1n=2n=3n=412本讲稿第十二页,共四十六页13本讲稿第十三页,共四十六页8.2 Fractal PropertiesvF has a fine structure,ie detail on arbitrarily small scales.vF has too irregular to be described in traditional geometrical language,both locally and globally.vOften F has some form of self-similarity,perhaps appro
5、ximate or statistical.vUsually,the fractal dimension of F is greater than its topological dimension.vIn most cases of interest of F is defined in a very simple way,perhaps recursively.(递归迭代)(递归迭代)14本讲稿第十四页,共四十六页8.3 Fractal Dimension15本讲稿第十五页,共四十六页vFractal similarity dimension:the straight-line segme
6、nt scale number length (r)(N)1/2 2 1 1/3 3 1 1/n n 1 1=Nr116本讲稿第十六页,共四十六页square (s=1)scale number area (r)(N)(s)1/2 4 1 1/3 9 1 1/n n2 1 1=Nr2 17本讲稿第十七页,共四十六页 a cube (v=1)scale number volume (r)(N)(s)1/2 23 1 1/3 33 1 1/n n3 1 1=Nr318本讲稿第十八页,共四十六页r scaling factor N the number of subparts NrD=1 D=N/(
7、1/r)19本讲稿第十九页,共四十六页20本讲稿第二十页,共四十六页 initiator start with a given geometric shape8.4 Geometric Construction of Deterministic Self-Similar Fractals generator subparts of the initiator are replaced with a pattern21本讲稿第二十一页,共四十六页 Basic idea:construction of the von koch each segment in(1)is replaced by an
8、 exact copy of the entire figure,shrunk by a factor of 3.The same process is applied to the segments in(2)to generate those in(3).22本讲稿第二十二页,共四十六页600-1200600(xs,ys)Angle:0 counterclockwise direction0 clockwise direction23本讲稿第二十三页,共四十六页global variables:int th;current value of float x,y;x,y coordinate
9、s float d;the length of each segment d=L/mn m:等分数 24本讲稿第二十四页,共四十六页Void Generate koch(n)/n:recursive depth if(n=0)x+=d*cos(th*3.14159/180)y+=d*sin(th*3.14159/180)line to(x,y);return;Generate koch(n-1);th+=60;Generate koch(n-1);th-=120;Generate koch(n-1);th+=60;Generate koch(n-1);25本讲稿第二十五页,共四十六页n=0 d
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