This thesis brought a lot of attention to things I have always taken for granted in art programs and graphics related software. One of these examples I never thought about is the accuracy and reproducibility/consistency of high quality text/ type faces. Screen resolutions have improved so much over the course of the past 30 years, allowing for the intricacies of different fonts to really come across. Rescaling/resizing different fonts and texts was always second nature and embedded in word processing tools, but reading the section on how rectangular convolution needed to be applied in order for this seemingly “basic” concept made me appreciative of how much mathematical work was put into designing the tools I use today.

Many of the animation principles were based in physics mechanics equations to simulate the dynamics of the text. Similarly, the distortion matrices to map a text to it’s representation in a distorted space showed the underlying technical detail required for many graphics techniques. I also found this cool because a lot of the same principles apply to what I am doing in another one of my classes, Computational & Digital Photograhpy. For one of the assignments we also wrote code to distort and morph an image into a new image space based on a transformation matrix like in the text and used bilenear interpolation to reconstruct it. It probably sounds silly, but I had this mental distinction between text and image, but this thesis and the recent readings on typefaces/kinetic typography are making me realize that text in the context of fonts and digital media relies upon many of the same graphics techology and tools as images/image processing.