Steven L Tanimoto
Computation with images, including data representations, algorithms, an introduction to programming in Python, and the design of games that involve images. Concepts include geometric and color transformations, filtering, data compression, fractals, and programming techniques.
Student learning goals
Understand how digital images are represented, including color models, sampling, quantization and compression.
Learn to program in the Python language.
Gain fluency in expressing transformations of images for visual effects.
Produce a personal portfolio of digital images that reflect creativity or illustrate a range of image-processing techniques.
Gain experience in a group project to develop an application of image computing.
General method of instruction
A combination of lectures, in-class activities, lab exercises, computer-based assignments and projects.
Basic familiarity with one of the standard computing platforms, such as Windows, MacOS or Linux.
Class assignments and grading
Two kinds of assignments: computer-based (e.g., image processing) and non-computer-based (pencil and paper). Also, a group project that involves developing a computer program in the Python language.
Regular assignments: 35%, projects: 35%, labs: 10%, two quizzes at 10 percent each: 20%. (No final exam in the Spring, 2013 offering)