Lenz, Reiner.
Group Theoretical Methods in Image Processing [electronic resource] / by Reiner Lenz. - Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. - X, 142 p. online resource. - Lecture Notes in Computer Science, 413 0302-9743 ; . - Lecture Notes in Computer Science, 413 .
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.
9783540469476
10.1007/3-540-52290-5 doi
Computer science.
Computer vision.
Optical pattern recognition.
Group theory.
Computer Science.
Pattern Recognition.
Image Processing and Computer Vision.
Group Theory and Generalizations.
Q337.5 TK7882.P3
006.4
Group Theoretical Methods in Image Processing [electronic resource] / by Reiner Lenz. - Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. - X, 142 p. online resource. - Lecture Notes in Computer Science, 413 0302-9743 ; . - Lecture Notes in Computer Science, 413 .
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.
9783540469476
10.1007/3-540-52290-5 doi
Computer science.
Computer vision.
Optical pattern recognition.
Group theory.
Computer Science.
Pattern Recognition.
Image Processing and Computer Vision.
Group Theory and Generalizations.
Q337.5 TK7882.P3
006.4