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Orthogonal Image Moments for Human-Centric Visual Pattern Recognition [electronic resource] /

By: Contributor(s): Material type: TextTextSeries: Cognitive Intelligence and RoboticsPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XII, 149 p. 58 illus., 42 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789813299450
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006 23
LOC classification:
  • TA1501-1820
  • TA1634
Online resources:
Contents:
1 Introduction -- 2 Image Moments -- 3 Face Recognition -- 4 Expression Recognition -- 5 Fingerprint Classification -- 6 Iris Recognition -- 7 Hand Gesture Recognition -- 8 Conclusion.
In: Springer Nature eBookSummary: Instead of focusing on the mathematical properties of moments, this book is a compendium of research that demonstrates the effectiveness of orthogonal moment-based features in face recognition, expression recognition, fingerprint recognition and iris recognition. The usefulness of moments and their invariants in pattern recognition is well known. What is less well known is how orthogonal moments may be applied to specific problems in human-centric visual pattern recognition. Unlike previous books, this work highlights the fundamental issues involved in moment-based pattern recognition, from the selection of discriminative features in a high-dimensional setting, to addressing the question of how to classify a large number of patterns based on small training samples. In addition to offering new concepts that illustrate the use of statistical methods in addressing some of these issues, the book presents recent results and provides guidance on implementing the methods. Accordingly, it will be of interest to researchers and graduate students working in the broad areas of computer vision and visual pattern recognition.
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1 Introduction -- 2 Image Moments -- 3 Face Recognition -- 4 Expression Recognition -- 5 Fingerprint Classification -- 6 Iris Recognition -- 7 Hand Gesture Recognition -- 8 Conclusion.

Instead of focusing on the mathematical properties of moments, this book is a compendium of research that demonstrates the effectiveness of orthogonal moment-based features in face recognition, expression recognition, fingerprint recognition and iris recognition. The usefulness of moments and their invariants in pattern recognition is well known. What is less well known is how orthogonal moments may be applied to specific problems in human-centric visual pattern recognition. Unlike previous books, this work highlights the fundamental issues involved in moment-based pattern recognition, from the selection of discriminative features in a high-dimensional setting, to addressing the question of how to classify a large number of patterns based on small training samples. In addition to offering new concepts that illustrate the use of statistical methods in addressing some of these issues, the book presents recent results and provides guidance on implementing the methods. Accordingly, it will be of interest to researchers and graduate students working in the broad areas of computer vision and visual pattern recognition.

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