Mathematical Methods in Computer Vision

The book "Mathematical Methods in Computer Vision" offers a comprehensive analysis of the mathematical methods used in computer vision. It is based on the essential contributions from two IMA workshops that took place in the fall of 2000. In recent years, significant progress has been made in applying complex mathematical theories to solve problems in image processing. Topics covered include image smoothing, noise reduction, image enhancement, morphology, image compression, and segmentation. The work highlights various mathematical approaches, including nonlinear partial differential equations, stochastic and statistical methods, as well as signal processing techniques. The importance of shape theory is emphasized, as it plays a central role between high-level and low-level vision. Additionally, applications in areas such as optical character recognition, printed circuit board inspection, and motion detection are discussed.