Group Theoretical Methods in Image Processing [electronic resource] / by Reiner Lenz.

By: Lenz, Reiner [author.]Contributor(s): SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 413Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1990Description: X, 142 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540469476Subject(s): Computer science | Computer vision | Optical pattern recognition | Group theory | Computer Science | Pattern Recognition | Image Processing and Computer Vision | Group Theory and GeneralizationsAdditional physical formats: Printed edition:: No titleDDC classification: 006.4 LOC classification: Q337.5TK7882.P3Online resources: Click here to access online
Contents:
Preliminaries -- Representations of groups -- Representations of somes matrix groups -- Fourier series on compact groups -- Applications.
In: Springer eBooksSummary: In this volume the author gives an introduction to the theory of group representations and their applications in image science. The main feature of the presentation is a systematic treatment of the invariance principle in image processing and pattern recognition with the help of group theoretical methods. The invariance properties of a problem often largely define the solution to the problem. Invariance principles are well known in theoretical physics but their use in image processing is only a few years old. The reader will find that group theory provides a unifying framework for many problems in image science. The volume is based on graduate-level lectures given by the author, and the book is intended for students and researchers interested in theoretical aspects of computer vision.
Item type: E-BOOKS
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Preliminaries -- Representations of groups -- Representations of somes matrix groups -- Fourier series on compact groups -- Applications.

In this volume the author gives an introduction to the theory of group representations and their applications in image science. The main feature of the presentation is a systematic treatment of the invariance principle in image processing and pattern recognition with the help of group theoretical methods. The invariance properties of a problem often largely define the solution to the problem. Invariance principles are well known in theoretical physics but their use in image processing is only a few years old. The reader will find that group theory provides a unifying framework for many problems in image science. The volume is based on graduate-level lectures given by the author, and the book is intended for students and researchers interested in theoretical aspects of computer vision.

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