Image Analysis
3,5 ECTS
Aim: This course covers the most popular techniques used in image analysis. We study the fundamental problem of image segmentation, which consists in separating objects in the foreground of a given image from its background, and also separating objects one to each other. This problem is formulated both in the classical framework of optimization (functional minimization), and in the frequency domain for textured segmentation. Various measurements techniques (such as perimeter, surface, volume, or diameter estimation for instance) are then presented. Direct applications of wavelet theory and Fourier analysis are also considered.
Content:
- measurements (2D, 3D)
- segmentation based on functional minimization
- application of linear methods (wavelet, FFT)