Genetic Art is a way to describe processes where genetic selection procedures are applied to computer-generated media, the selection criteria being based on aesthetical choices. In other words, think of yourself as a Mendel-wannabe of the digital era, one that works with images instead of peas. Ready to experiment?
The link above will direct you to a web-friendly, ready-to-use classic Genetic Art program. As soon as you load the page, you will see a number of images, each in its own window. See any that you like? Then click on the Action Menu and make two of them take over the left and right selections. Notice that they will appear in the bottom-right corner of the screen, just to the sides of the Breed pictures button. So now click on that button and voilá! that´s the first kid, congratulations!
What next? I suggest two things: first, unclutter the screen by closing the windows containing images that you don’t like. Second, click a few more times on the breed button, since the same two parents can often yield very different children. At any given point you can change any of the parents, and in case you didn’t like any of the starting images there’s a convenient button that will create random images; reloading the page will give you an entirely new set of images to work with. Finally, when you get to an image you like, you can make a larger render via the Action Menu. Unfortunately I haven’t found any option to save the images, so I use the “print screen” option in the computer, then crop the capture (as in the picture above).
At the core of the program, the images are generated by means of mathematical formulas. Actually, when you breed two images, two things happen:
a random subexpression of one is replaced by a random subexpression of the other
mutation is applied which changes one of the operations in the formula
If you look once more in the Actions Menu, you´ll see that there´s an option to edit the formula for any image, so there´s room for all sorts of genetic engineering, if you´re into that 😛
Finally, in case you liked this nice application, I suggest that you go try Kandid. It follows the same principles, but it is much more thorough -and a bit more complex, though much slower- in its process.