Jason M. Kinser

Image Operators (eBook, PDF)

Image Processing in Python

• Format: PDF

Produktbeschreibung

This book will provide a unified theoretical foundation of image analysis procedures with accompanied Python® computer scripts to precisely describe the steps in image processing applications. Linkage between required scripts and theory through operators will be presented.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 365
• Erscheinungstermin: 10. Oktober 2018
• Englisch
• ISBN-13: 9780429835940
• Artikelnr.: 54362384

Autorenporträt

Jason M Kinser, DSc, has been an associate professor at George Mason University for more than 18 years teaching courses in physics, computational science, bioinformatics and forensic science. Recently, he converted the traditional university physics course into an active learning technology environment at GMU. His research interests include modern teaching techniques, more effective methods in text-based education, image operators and analysis, pulse image processing and multi-domain data analysis. This book was born from a desire to engage students in physics education and to find ways of reducing the external costs that both students and institutions incur within the traditional education framework.Jason M Kinser, DSc, has been an associate professor at George Mason University for more than 18 years teaching courses in physics, computational science, bioinformatics and forensic science. Recently, he converted the traditional university physics course into an active learning technology environment at GMU. His research interests include modern teaching techniques, more effective methods in text-based education, image operators and analysis, pulse image processing and multi-domain data analysis. This book was born from a desire to engage students in physics education and to find ways of reducing the external costs that both students and institutions incur within the traditional education framework.

Inhaltsangabe

PART I Image Operators. 1 Introduction. 2 Operator Nomenclature. 3
Scripting in Python. 4 Digital Images. 5 Color. PART II Image Space
Manipulations. 6 Geometric Transformations. 7 Image Morphing. 8 Principle
Component Analysis. 9 Eigenimages. PART III Frequency Space Manupulations.
10 Image Frequemncies. 11 Filtering in Frequency Space. 12 Correlations.
PART IV Texture and Shape. 13 Edge Detection. 14 Hough Transforms. 15
Noise. 16 Texture Recognition. 17 Gabor Filtering. 18 Describing Shape.
PART V Basis. 19 Basis Sets. 20 Pulse Images and Autowaves. Appendix A
Operators. Appendix B Operators in Symbolic Order. Appendix C Lengthy
Codes. Bibliography.