TY - BOOK ID - 32940956 TI - A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition AU - Prandi, Dario. AU - Gauthier, Jean-Paul. PY - 2018 SN - 331978482X 3319784811 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Mathematics. KW - Computer graphics. KW - Harmonic analysis. KW - Computer science KW - Computer mathematics. KW - Abstract Harmonic Analysis. KW - Mathematical Applications in Computer Science. KW - Computer Imaging, Vision, Pattern Recognition and Graphics. KW - Image reconstruction KW - Pattern perception KW - Mathematical models. KW - Design perception KW - Pattern recognition KW - Form perception KW - Perception KW - Figure-ground perception KW - Image restoration KW - Reconstruction, Image KW - Restoration, Image KW - Image processing KW - Computer vision. KW - Machine vision KW - Vision, Computer KW - Artificial intelligence KW - Pattern recognition systems KW - Analysis (Mathematics) KW - Functions, Potential KW - Potential functions KW - Banach algebras KW - Calculus KW - Mathematical analysis KW - Mathematics KW - Bessel functions KW - Fourier series KW - Harmonic functions KW - Time-series analysis KW - Computer science—Mathematics. KW - Optical data processing. KW - Optical computing KW - Visual data processing KW - Bionics KW - Electronic data processing KW - Integrated optics KW - Photonics KW - Computers KW - Computer mathematics KW - Optical equipment UR - https://www.unicat.be/uniCat?func=search&query=sysid:32940956 AB - This book proposes a semi-discrete version of the theory of Petitot and Citti-Sarti, leading to a left-invariant structure over the group SE(2,N), restricted to a finite number of rotations. This apparently very simple group is in fact quite atypical: it is maximally almost periodic, which leads to much simpler harmonic analysis compared to SE(2). Based upon this semi-discrete model, the authors improve on previous image-reconstruction algorithms and develop a pattern-recognition theory that also leads to very efficient algorithms in practice. ER -