Jonathan McCabe. Multiscale Turing Patterns. Jonathan McCabe | Bridges Math Art Galleries. McCabeism: turning noise into a thing of beauty | W:Blut. If you’ve seen any reality zoo/wild-life program you’ll recognize this. Five minutes into the show you’re confronted with a wounded, magnificent animal, held in captivity so its caretakers can nurture and feed it. And inevitably, after three commercial breaks, they release it, teary-eyed, back into the wild. It’s a pivotal moment that turns their leopard into anyone’s/no one’s leopard.
And as much as they like to see the animal run free, it hurts that only they know that that is the leopard that Bruce bottle-fed. It’s similar with code. Anyway, most of us don’t have to worry about this, I gladly share it all, because real innovation that’s truly worthy of attribution is rare. There is however an idea, an algorithm out there that was shared by its creator Jonathan McCabe that is worthy of true attribution, that falls outside the realm of “anyone could’ve done it”. Turns out I was being silly. Feel free to use it in your own exploration of McCabeism. Life of a Lab Rat: Art from Turing Patterns. Turing patterns are the more common name for "reaction-diffusion patterns" which are found in abundance throughout the natural world. They are formed by a simple system of cell-cell communication; cells secrete signals that mean nearby cells will become the same as them, whereas far away cells will differentiate.
In terms of colour this leads to dots and stripes patterns, which are found in almost all patterning systems in nature: Simple Turing patterns, from Wikipedia Commons These patterns can be generated electronically as well, by using computer models. The next stage is to create a range of different scales, to create fractal-type Turing patterns where each cell recognizes both the shade and the scale of the surrounding cells. As the overall look is still quite square Jonathan added an imposed cyclic symmetry to the program, in the search for a more 'biological' look. Diatomaceous6 from Jonathan McCabe on Vimeo. Www.wblut.com/constructs/McCabeism/TuringPattern.pde. Www.wblut.com/constructs/McCabeism/McCabeism.pde. 20100708a – Zoom.it – Image 15w5. Image0017. McCabeism : Built with Processing.
Recommended Version 7 Update 51 Select the file according to your operating system from the list below to get the latest Java for your computer. By downloading Java you acknowledge that you have read and accepted the terms of the end user license agreement <p><span class="termhighlight">In order to optimize your experience and provide you with accurate messages, please enable javascript in your browser for the duration of your Java installation. </span></p> What is Java? Java allows you to play online games, chat with people around the world, calculate your mortgage interest, and view images in 3D, just to name a few. It's also integral to the intranet applications and other e-business solutions that are the foundation of corporate computing. » What is Java FAQ» More information about Java. Softology - Visions Of Chaos. "Vision of Chaos is a great Programm!
I have many, many hour's fun. Thank you very much. " "It is one of my favourite and most powerful pieces of software" "I'm a long-time user and big fan of the software, and find it more intuitive and full-featured than just about any other fractal generator out there. I'm also extremely happy that you've continued updating Visions Of Chaos" "Visions of Chaos is a remarkable and easy to use fractal and chaos program.
"It is a 'mathematical Leeuvenhoek microscope' looking at objects never before seen. "I appreciate your efforts on Visions of Chaos, a very fine program indeed! " "I have your software which is OUTSTANDING!!! " "by far i think it is the only program which can do heightmap rendering easily" "a most excellent software" "VOC is a very fine program deserving wider recognition" "Impressive and beautiful 3D worlds are revealed with your software" "Visons Of Chaos is a great fractal program. "Voc reminds me of wolfenstein and the doom games. Softology - Visions Of Chaos Gallery. Blur. Blurring is a very powerful operation used in image processing and procedural texture generation. Blurs involve calculating weighted averages of areas of pixels in a source image for each pixel of the final blurred image. Computing these weighted averages can be very expensive.
For example, to create a blurry image you may need to touch hundreds of pixels for every pixel that you output. In this text, I'll show you some tricks for performing blurs very quickly. Basic blur First let's take a look at a simple blurring algorithm: function Blur (source, dest, radius) { for (y = 0; y < height; ++y) { for (x = 0; x < width; ++x) { total = 0 for (ky = -radius; ky <= radius; ++ky) for (kx = -radius; kx <= radius; ++kx) total += source(x + kx, y + ky) dest(x, y) = total / (radius * 2 + 1) ^ 2 } } } This function blurs a source image and places the result in the destination image.
Instead of just computing the average, many blurs use a weight for each pixel. Separate horizontal and vertical. Computer Vision – The Integral Image « Computer Science: Source. September 3, 2010 by Badgerati The Integral Image or Summed Area Table, was first introduced to us in 1984, but wasn’t properly introduced to the world of Computer Vision till 2001 by Viola and Jones with the Viola-Jones Object Detection Framework. The Integral Image is used as a quick and effective way of calculating the sum of values (pixel values) in a given image – or a rectangular subset of a grid (the given image). It can also, or is mainly, used for calculating the average intensity within a given image. If one wants to use the Integral Image, it is normally a wise idea to make sure the image is in greyscale first. So, how does it work? So, let us start off with the basics.
What is really good about the Summed Area Table, is that we are actually able to construct it with only one pass over of the given image. Here is a better example, take the following image and its corresponding Summed Area Table: On the left we have the given image, with its corresponding pixel values. Like this: Summed area table. A summed area table is a data structure and algorithm for quickly and efficiently generating the sum of values in a rectangular subset of a grid. In the image processing domain, it is also known as an integral image. It was first introduced to computer graphics in 1984 by Frank Crow for use with mipmaps. In computer vision it was first prominently used within the Viola–Jones object detection framework in 2002.
However, historically, this principle is very well known in the study of multi-dimensional probability distribution functions, namely in computing 2D (or ND) probabilities (area under the probability distribution) from the respective cumulative distribution functions.[1] The algorithm[edit] As the name suggests, the value at any point (x, y) in the summed area table is just the sum of all the pixels above and to the left of (x, y), inclusive:[2][3] Finding the sum of a rectangular area over the rectangle spanned by A, B,C and D is just Extensions[edit] with in where and .
Or Lecture videos. Fast Lens Blur Kernel. Kyle McDonald. Welcome to jonathanmccabe.com. 2010 Bridges Conference | Bridges Math Art Galleries. Nccasymposium.bournemouth.ac.uk/SYMPOSIUM_2012.htm. Since the advent of motion pictures, filmmakers have endeavored to transport the viewers to fantastic worlds, different times, and far away places.
Tools and techniques for achieving these illusions have evolved during the short history of the cinematic art form such as miniature sets, stop-motion animation, computer generated characters and environments, among many others. In regarding to it, my talk will discuss Matte paintings are one of the oldest and most effective special effects. These highly detailed paintings have a tradition that stems from hundreds of years ago. Proceeding through with examples like, flat planes of wood and canvas were painted to add depth and realism to a stage set; during the Renaissance master artists created the most realistic art of their time using newly developed proficiency in perspective, perception, light, shadow, and color.
Online Notes. How do I separate an imported mesh? The methods I have always done is to first take the File SOP and pass it to a "Reverse" SOP if it is from a .obj from Maya. This reverses normals and such so that it displays correctly in Houdini. If the model still looks messed up, you may need to connect it to a "Facet" SOP to consolidate points, cusp (harden edges based on angle), and/or recompute normals, etc., but be careful of this if you need to rely on the different meshes being seperate like in my second method below. Now for this first method to work, the input geometry needs to have seperate groups in it that are generally created based on material assignments in Maya or whatever. You can middle mouse click (and hold) on the File SOP to see if these exist. If there are seperate groups I connect the node to a "Delete" SOP in the network pane. You can then operate on all of these seperately and then combine them later with a "Merge" SOP.
Hope this helps. Craig. Algorithmic art. Algorithmic art, also known as algorithm art, is art, mostly visual art, of which the design is generated by an algorithm. Algorithmic artists are sometimes called algorists. Overview[edit] "Octopod" by Mikael Hvidtfeldt Christensen. An example of algorithmic art produced with the software Structure Synth.
Algorithmic art, also known as computer-generated art, is a subset of generative art and is related to systems art. Fractal art is an example of algorithmic art. For an image of reasonable size, even the simplest algorithms require too much calculation for manual execution to be practical, and they are thus executed on either a single computer or on a cluster of computers. History[edit] Some of the earliest known examples of computer-generated algorithmic art were created by Georg Nees and Frieder Nake in the early 1960s. Aside from the ongoing work of Verostko and his fellow algorists, the next known examples are fractal artworks created in the mid to late 1980s. Algorists[edit] Evolutionary art. Artificial Evolution of the Cyprus Problem (2005) is an artwork created by Genco Gulan Evolutionary art is created using a computer.
The process starts by having a population of many randomly generated individual representations of artworks. Each representation is evaluated for its aesthetic value and given a fitness score. The individuals with the higher fitness scores have a higher chance of remaining in the population while individuals with lower fitness scores are more likely to be removed from the population. Evolutionary art is a branch of Generative art, which system is characterized by the use of evolutionary principles and natural selection as generative procedure.
In common with natural selection and animal husbandry, the members of a population undergoing artificial evolution modify their form or behavior over many reproductive generations in response to a selective regime. See also[edit] Further reading[edit] Conferences[edit] External links[edit] Definitions. Iñigo Quilez - fractals, computer graphics, mathematics, demoscene and more. Iñigo Quilez - vanilla :: fractals, comp... Spin by Andromeda Software Development. Generative Art | Syntopia | Page 2. As discussed in the previous part, formal grammars can be used to generate and manipulate text strings. The question is how this can be extended to generate pictures, movies, or music. One possibility would be to interpret the symbolic output as some sort of representation or encoding, which could be unfolded to create the final output. For instance it would be rather simple to create a grammar, which created an SVG XML file for output.
A wide used example of this approach is Lindenmayer systems, where the output is interpreted as a sort of ‘LOGO Turtle Graphics’. Lindenmayer Systems Lindenmayer Systems (or simply L-systems) are related to formal grammars, but in contrast to formal grammars which describe the syntax for the infinite number of sentences for a formal language, L-systems describe a generational process for manipulating text strings. In L-systems you iteratively apply all the production rules to the output of the previous iteration.
An example L-system: A-> B-A-B B-> A+B+A. William Latham. Form. Reaction-Diffusion. My thesis work was about creating synthetic texture using reaction-diffusion. Reaction-diffusion is a process in which two or more chemicals diffuse over a surface and react with one another to produce stable patterns. Reaction-diffusion can produce a variety of spot and stripe patterns, much like those found on many animals. Developmental biologists think that some of the patterns found in nature may be the result of reaction-diffusion processes. Often in computer graphics we want to add "texture" to an object, that is, some pattern of colors or bumps. Much of the work that I did was published in this article: "Generating Textures on Arbitrary Surfaces Using Reaction-Diffusion" Greg Turk Computer Graphics, Vol. 25, No. 4, pp. 289-298 July 1991 (SIGGRAPH '91) Postscript version of paper (4.0 Mbytes).
PDF version of paper (2.6 Mbytes). I also have my dissertation on-line: "Texturing Surfaces Using Reaction-Diffusion" Greg Turk, Ph.D. Tech Report TR94-035 Here are some images from this work: The Chemical Basis of Morphogenesis. The Chemical Basis of Morphogenesis is an article written by the English mathematician Alan Turing in 1952 describing the way in which non-uniformity (stripes, spots, spirals, etc.) may arise naturally out of a homogeneous, uniform state.[1] The theory (which can be called a reaction–diffusion theory of morphogenesis), has served as a basic model in theoretical biology,[2] and is seen by some as the very beginning of chaos theory.[3] [edit] Reaction–diffusion systems have attracted much interest as a prototype model for pattern formation. The above-mentioned patterns (fronts, spirals, targets, hexagons, stripes and dissipative solitons) can be found in various types of reaction-diffusion systems in spite of large discrepancies e.g. in the local reaction terms.
References[edit] Jump up ^ Turing, A. External links[edit] Turing, Alan M. (14 August 1952). Flowpi 2. 88, 208303 (2002): Spatial Resonances and Superposition Patterns in a Reaction-Diffusion Model with Interacting Turing Modes. Reaction-Diffusion in Houdini 10 apprentice. Rgba slisesix. Gray Scott 3D reaction diffusion system. Turing's Reaction-Diffusion Model of Morphogenesis.
This is a small companion piece to my page on L-systems. As mentioned there, in 1952 Alan Turing wrote a paper [2] proposing a reaction-diffusion model as the basis of the development of patterns such as the spots and stripes seen in animal skin. Inspired by the methods described in [1], I wrote the small applet that appears on this page. By entering different constants for the equations, it is possible to produce a variety of natural-looking textures.
Since the state of the system is initially random noise, repeating the computation with the same constants will produce a different image with a similar pattern. The algorithm behaves as if the "cells" were arranged on the surface of a torus, which results in textures that can be tiled seamlessly. Multi-stage Textures Many animals develop their coat patterns in stages. The Applet Source Code Java The applet requires that your browser support at least the Java 6 runtime. Blank Images Return to Home Page Return to Tickle Trunk Send Feedback. Branching morphogenesis. About | electric sheep. Epic conway's game of life. "Fluid Simulation with Turing Patterns" by Felix Woitzel. Generating textures on arbitrary surfaces using reaction-diffusion.
Allen Sanderson, Ph.D. - Projects.