A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition
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Beschreibung
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.
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.
Offers a cortical-inspired point of view on image processing Provides fast and efficient methods for image inpainting and recognition Presents a new theoretical framework for roto-translation invariant image recognition
Autor*in
Dario Prandi
Themen in »A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition«
Neurogeometry Abstract harmonic analysis Fourier descriptors Hypoelliptic diffusion Almost-periodic functions
Stimmen zu »A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition«
“The book is written in a very accessible fashion and the proposed methods are described in depth. It is suitable for graduate students and for researchers and professionals interested in image reconstruction and pattern recognition.” (Krzystof Gdawiec, zbMATH 1415.68007, 2019)
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