Serendipity

What are the chances of meeting a person in your life and the person becoming an important person in your life as your best friend, soul mate, or spouse, and even chances of being born and meeting your parents as your parents? The population in the world is 7,838,490,840 (at the time I researched) and adding up in every second. If you calculate all those chances out there in numbers, it is quite a mere chance out there to find relationships with someone that you already have in your life.

We often talk with terms like miracle, destiny, coincidence, and serendipity, to show the possibility of occurrence daily. Especially, the term ’serendipity’ means the fact of finding interesting or valuable things by chance, allowing chance finds. Serendipity is one of the words that I like in the sense of occurrence of discovery that gives excitement for unexpected events.

What would be the odds of having a roommate from Spain in Ireland and still keeping in touch after six years? What are the chances of meeting a guy from the Netherlands at your university in Korea and having a long-distance relationship for three years traveling back and forth between three countries, the Netherlands, Korea, and the USA?

The above fingerprint consists of the number of possibilities around me. Like the fact that everyone has different fingerprint shapes, everyone has different chances in life.

This random computer-generated image art is inspired by the many odds created daily in our lives. This project makes use of several computer science techniques and a simple algorithm, to automatically create random images based on a recursive principle with the use of mathematical functions. The program that generates the final (random) outputs in the shape of images, is provided with a couple of inputs. First of all, the shape of the output images is set. In this case 1024 by 1024 pixels. Furthermore, besides the size of the output, the image complexity is defined by the use of a range between 2 integers. The program randomly chooses a number within the range of these 2 numbers which will indicate the final complexity depth of the output. The higher the number, the more complex the final output. This complexity is represented by the number of recursions the program executes/runs. For each recursion, the program randomly chooses from a set of mathematical functions to determine the value for each pixel. In the end, these pixel values are converted to a certain color. The final output of the program is an array containing pixel values, which the computer can interpret as colors. These pixel values range between 0 and 255 and are correlated with each other based on the mathematical functions used during the random generation process. This correlation results in possible shapes and lines in the final output. The higher the complexity of an image, the more complex the shapes and lines are. The abstract and complex shapes are created by the different provided mathematical functions. Theoretically, this program can be executed countless times, without ever producing the same result since there is a close to an infinite amount of pixel value combinations ((1024*1024)*255)*9).

*This is a project done in teamwork.

Process