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Produktbeschreibungen
Kurzbeschreibung
This introductory textbook presents the modern signal processing concepts used in computer vision and image analysis in a systematic and mathematically coherent way. For the first time in a textbook on image processing, single direction, group direction, corners and edges, Hough transform, and motion estimation are developed in a principled way using direction tensors as the unifying concept. The topics presented include Hilbert spaces, the Fourier transform, scale analysis, direction fields, structure tensors, motion tensors, the Hough transform, grouping, and segmentation. Directional signal processing, an increasingly crucial element of computer vision for which neural circuits exist in human vision, is dealt with in depth by use of tensors. All chapters are richly illustrated, with color graphics from cover to cover; applications are studied in various fields, including biometric person authentication, texture analysis, optical character recognition, and motion estimation and tracking; and exercises help the sudent verify progress. Developed out of courses given by the author, this introductory textbook addresses advanced undergarduates as well as master and PhD students in computer science, engineering, mathematics, and in other disciplines where techniques from computer vision, image processing, visual computation and signal analysis are applied.
Synopsis
This introductory textbook presents the modern signal processing concepts used in computer vision and image analysis in a systematic and mathematically coherent way. For the first time in a textbook on image processing, single direction, group direction, corners and edges, Hough transform, and motion estimation are developed in a principled way using direction tensors as the unifying concept. The topics presented include Hilbert spaces, the Fourier transform, scale analysis, direction fields, structure tensors, motion tensors, the Hough transform, grouping, and segmentation. Directional signal processing, an increasingly crucial element of computer vision for which neural circuits exist in human vision, is dealt with in depth by use of tensors. All chapters are richly illustrated, with color graphics from cover to cover; applications are studied in various fields, including biometric person authentication, texture analysis, optical character recognition, and motion estimation and tracking; and exercises help the student verify progress.Developed out of courses given by the author, this introductory textbook addresses advanced undergraduates as well as master and PhD students in computer science, engineering, mathematics, and in other disciplines where techniques from computer vision, image processing, visual computation and signal analysis are applied.
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
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strong maths treatment
12. August 2007
Format:Gebundene Ausgabe
Bigun's book is an excellent way to delve into the intricacies of image analysis. The treatment is strongly mathematical. Involving the defining of Hilbert spaces and of operators within these spaces. Along with the use of tensors and minimising of residuals. The text starts from scratch, by considering an image and the RGB and HSV methods of representing that image. But the maths rapidly becomes quite sophisticated.
There is a definite connection with traditional statistical analysis of non-images. Concepts like power spectrum and regression analysis are common to both treatments. The book also has a good treatment of curvilinear coordinates. Well suited to studying images like those given in several of the text's examples.
The book only lightly touches on facial analysis. This is an entire subject of its own. There is a brief mention of eigenfaces, but you should turn to other texts devoted to studying faces, if that is your interest.
There is a definite connection with traditional statistical analysis of non-images. Concepts like power spectrum and regression analysis are common to both treatments. The book also has a good treatment of curvilinear coordinates. Well suited to studying images like those given in several of the text's examples.
The book only lightly touches on facial analysis. This is an entire subject of its own. There is a brief mention of eigenfaces, but you should turn to other texts devoted to studying faces, if that is your interest.
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