How do I compute the fractal dimension of the Koch curve using Matlab?

In summary, the conversation is about coding two programs related to obtaining the fractal dimension of the Koch curve. One program uses the method of box counting dimension and the other uses the Grassberger-Procaccia algorithm. The equations for the box counting dimension and the Grassberger Procaccia or correlation dimension are discussed, but there is uncertainty on how to implement them. A solution is suggested using a Matlab function from the MathWorks file exchange, which involves padding the image and using the least squares method to calculate the Haussdorf fractal dimension. Questions are encouraged.
  • #1
crazy2006
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Homework Statement



I have a problem trying to code these two programs, one is related to the obtain the fractal dimension of the Koch curve by using the method of the box counting dimension and also using the Grassberger-Procaccia algorithm

Homework Equations


For the box counting dimension is just the lim N(l)/l as l goes to zero, so first I should generate a meshgrid of the Koch curve and count the number of filled boxes, how I do that in matlab?
For the Grassberger Procaccia or correlation dimension I have reviewed the formula, but no idea how to implement it

The Attempt at a Solution


I have not really a code to follow here, so any help it would be great
 
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  • #2
I have submitted an http://www.mathworks.com/matlabcentral/fileexchange/30329-hausdorff-box-counting-fractal-dimension" to compute the fractal dimension Matlab's files exchange.

The function takes as input a binary image I. In this image, nonzero pixels belong to an object (e.g. the kock curve) and 0 pixels constitute the background.

Basically, the algorithm consists in the following steps:

1 - Pad the image with background pixels so that its dimensions are a power of 2.
2 - Set the box size 'e' to the size of the image.
3 - Compute N(e), which corresponds to the number of boxes of size 'e' which contains at least one object pixel.
4 - If e > 1 then e = e / 2 and repeat step 3.
5 - Compute the points log(N(e)) x log(1/e) and use the least squares method to fit a line to the points.
6 - The returned Haussdorf fractal dimension D is the slope of the line.

If you have any questions, you are welcome to ask.
 
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1. What is a fractal dimension?

A fractal dimension is a mathematical concept that measures the complexity of a geometric pattern or object. It is a non-integer value that falls between the dimensions of a line (1D) and a plane (2D).

2. How is the fractal dimension calculated in Matlab?

In Matlab, the fractal dimension can be calculated using various algorithms, such as the box-counting method, the correlation dimension, or the information dimension. These algorithms involve measuring the number of boxes or spheres needed to cover the fractal pattern at different scales, and then using a mathematical formula to calculate the dimension.

3. What are some applications of calculating fractal dimension?

Fractal dimension has various applications in different fields such as image processing, signal analysis, and data compression. It can also be used to characterize natural phenomena, such as coastlines, clouds, and mountain ranges, and to study the complexity of biological structures.

4. Can fractal dimension be used to identify patterns in data?

Yes, fractal dimension can be used as a tool to identify and analyze patterns in data. It can reveal hidden relationships and structures that may not be apparent through traditional methods of data analysis, leading to a better understanding of complex systems.

5. Are there any limitations to using fractal dimension in Matlab?

One limitation of using fractal dimension in Matlab is that it is sensitive to noise and errors in data. This can lead to inaccurate results if not properly accounted for. Additionally, the choice of algorithm and parameters can also affect the calculated fractal dimension, so it is important to carefully select the appropriate method for the specific application.

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