Category Archives: image
A fundamental artifact of any digital imaging device is that it samples an infinite reality and encodes it in a finite data-set. A digital image is essentially a series of color values and its definition is limited by the size of the data it holds (number of pixels and color depth). The experimental software FIG exploits this artifact and attempts to iterate through all the possible color combinations a digital canvas can hold. Since any image can be digitized, we should also expect that any and every representation can be found in one of these possible color combinations. FIG guarantees that with enough time, it will eventually generate every possible image.
At the present time this only works in a theoretical level, as even when running at 60 iterations per second, it would require a little less than 10 billion years (or almost the age of the known universe) to iterate through all the images of an 8×8 pixels image and just 2 colors. But as the processing power of computers keeps increasing alongside the fast progress in quantum computing, we may eventually be able to brute force the generation of all images and filter the meaningful ones out of the chaos. In a potential future version of this software, the output images can be passed into an image recognition algorithm which would identify, aggregate and categorize human recognizable results and allow us to see everything that can be seen.
So will happen if and when we get to that point?
Could this ever challenge human creativity?
Who would own the intellectual property of all the pictures?
For more information and to use the Finite Image Generator, please visit fig.ch3.gr
This series of images is the second iteration of an experiment in digital reconstruction of portrait photography. It is an attempt to create a hybrid between hand drawn and procedurally generated image.
A custom software was implemented in processing, which provides the user with a set of digital brushes. Influenced by the LOGO programming language, each brushstroke spawns agents that move within the blank canvas, to create an image with the trails they leave behind. Each brush is a set of different instructions for the agents to follow. These instructions reference the color of an input image to determine the trajectory, behavior but also the color of their trails. The user’s only creative decision is where and how to apply the brushstrokes within the image. Using a tablet, the speed, tilt and the pressure of the pen change various characteristics of the tool, creating expressive brushstrokes.
Along with painting the images, the implementation of the tool played an equal role to the whole creative process. Both stages required experimentation to define the aesthetic of the final images.
A demonstration of the software in operation.
Series of images using with the first version of the tool.