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9780470699874: Moments and Moment Invariants in Pattern Recognition
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MOMENTS AS PROJECTIONS OF AN IMAGE S INTENSITY ONTO A PROPER POLYNOMIAL BASIS CAN BE APPLIED TO MANY DIFFERENT ASPECTS OF IMAGE PROCESSING. THESE INCLUDE INVARIANT PATTERN RECOGNITION, IMAGE NORMALIZATION, IMAGE REGISTRATION, FOCUS/ DEFOCUS MEASUREMENT, AND WATERMARKING. THIS BOOK PRESENTS A SURVEY OF BOTH RECENT AND TRADITIONAL IMAGE ANALYSIS AND PATTERN RECOGNITION METHODS, BASED ON IMAGE MOMENTS, AND OFFERS NEW CONCEPTS OF INVARIANTS TO LINEAR FILTERING AND IMPLICIT INVARIANTS. IN ADDITION TO THE THEORY, ATTENTION IS PAID TO EFFICIENT ALGORITHMS FOR MOMENT COMPUTATION IN A DISCRETE DOMAIN, AND TO COMPUTATIONAL ASPECTS OF ORTHOGONAL MOMENTS. THE AUTHORS ALSO ILLUSTRATE THE THEORY THROUGH PRACTICAL EXAMPLES, DEMONSTRATING MOMENT INVARIANTS IN REAL APPLICATIONS ACROSS COMPUTER VISION, REMOTE SENSING AND MEDICAL IMAGING.   KEY FEATURES:   PRESENTS A SYSTEMATIC REVIEW OF THE BASIC DEFINITIONS AND PROPERTIES OF MOMENTS COVERING GEOMETRIC MOMENTS AND COMPLEX MOMENTS. CONSIDERS INVARIANTS TO TRADITIONAL TRANSFORMS TRANSLATION, ROTATION, SCALING, AND AFFINE TRANSFORM – FROM A NEW POINT OF VIEW, WHICH OFFERS NEW POSSIBILITIES OF DESIGNING OPTIMAL SETS OF INVARIANTS. REVIEWS AND EXTENDS A RECENT FIELD OF INVARIANTS WITH RESPECT TO CONVOLUTION/BLURRING. INTRODUCES IMPLICIT MOMENT INVARIANTS AS A TOOL FOR RECOGNIZING ELASTICALLY DEFORMED OBJECTS. COMPARES VARIOUS CLASSES OF ORTHOGONAL MOMENTS (LEGENDRE, ZERNIKE, FOURIER–MELLIN, CHEBYSHEV, AMONG OTHERS) AND DEMONSTRATES THEIR APPLICATION TO IMAGE RECONSTRUCTION FROM MOMENTS. OFFERS COMPREHENSIVE ADVICE ON THE CONSTRUCTION OF VARIOUS INVARIANTS ILLUSTRATED WITH PRACTICAL EXAMPLES. INCLUDES AN ACCOMPANYING WEBSITE PROVIDING EFFICIENT NUMERICAL ALGORITHMS FOR MOMENT COMPUTATION AND FOR CONSTRUCTING INVARIANTS OF VARIOUS KINDS, WITH ABOUT 250 SLIDES SUITABLE FOR A GRADUATE UNIVERSITY COURSE.

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Críticas:
"This text is a little gem in the vast amount of literature on pattern recognition...In conclusion, this is an excellent text on pattern recognition that I highly recommend to practitioners and students in signal and image processing." ( Computing Reviews , October 2010)
Reseña del editor:
Moments as projections of an image's intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms -- translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.

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  • EditorialJohn Wiley & Sons Inc
  • Año de publicación2009
  • ISBN 10 0470699876
  • ISBN 13 9780470699874
  • EncuadernaciónTapa dura
  • Número de páginas312
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Descripción Condición: New. Moments and Moment Invariants in Pattern Recognition presents a survey of fundamental and topical pattern recognition methods based on image moments. The authors expound on the establishment of the use of invariant moments in pattern recognition and continue by presenting a systematic review of the basic definitions and properties of moments. Num Pages: 312 pages, Illustrations. BIC Classification: UYQP. Category: (P) Professional & Vocational. Dimension: 250 x 190 x 22. Weight in Grams: 650. . 2009. . . . . Nº de ref. del artículo: V9780470699874

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Descripción Condición: New. Moments and Moment Invariants in Pattern Recognition presents a survey of fundamental and topical pattern recognition methods based on image moments. The authors expound on the establishment of the use of invariant moments in pattern recognition and continue by presenting a systematic review of the basic definitions and properties of moments. Num Pages: 312 pages, Illustrations. BIC Classification: UYQP. Category: (P) Professional & Vocational. Dimension: 250 x 190 x 22. Weight in Grams: 650. . 2009. . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9780470699874

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Descripción Hardcover. Condición: new. Hardcover. Moments as projections of an images intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments.Considers invariants to traditional transforms translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants.Reviews and extends a recent field of invariants with respect to convolution/blurring.Introduces implicit moment invariants as a tool for recognizing elastically deformed objects.Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments.Offers comprehensive advice on the construction of various invariants illustrated with practical examples.Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest. Moments and Moment Invariants in Pattern Recognition presents a survey of fundamental and topical pattern recognition methods based on image moments. The authors expound on the establishment of the use of invariant moments in pattern recognition and continue by presenting a systematic review of the basic definitions and properties of moments. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780470699874

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Descripción Condición: New. Moments as projections of an image s intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and. Nº de ref. del artículo: 556557753

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Descripción Hardcover. Condición: new. Hardcover. Moments as projections of an images intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments.Considers invariants to traditional transforms translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants.Reviews and extends a recent field of invariants with respect to convolution/blurring.Introduces implicit moment invariants as a tool for recognizing elastically deformed objects.Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments.Offers comprehensive advice on the construction of various invariants illustrated with practical examples.Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest. Moments and Moment Invariants in Pattern Recognition presents a survey of fundamental and topical pattern recognition methods based on image moments. The authors expound on the establishment of the use of invariant moments in pattern recognition and continue by presenting a systematic review of the basic definitions and properties of moments. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9780470699874

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Descripción Hardcover. Condición: new. Hardcover. Moments as projections of an images intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments.Considers invariants to traditional transforms translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants.Reviews and extends a recent field of invariants with respect to convolution/blurring.Introduces implicit moment invariants as a tool for recognizing elastically deformed objects.Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments.Offers comprehensive advice on the construction of various invariants illustrated with practical examples.Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest. Moments and Moment Invariants in Pattern Recognition presents a survey of fundamental and topical pattern recognition methods based on image moments. The authors expound on the establishment of the use of invariant moments in pattern recognition and continue by presenting a systematic review of the basic definitions and properties of moments. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9780470699874

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