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Invariants For Pattern Recognition And Classification
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Book Synopsis Invariants for Pattern Recognition and Classification by : Marcos A. Rodrigues
Download or read book Invariants for Pattern Recognition and Classification written by Marcos A. Rodrigues and published by World Scientific. This book was released on 2000 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was conceived from the realization that there was a need to update recent work on invariants in a single volume providing a useful set of references and pointers to related work. Since the publication in 1992 of J.L. Mundy and A. Zisserman's Geometric Invariance in Computer Vision, the subject has been evolving rapidly. New approaches to invariants have been proposed and novel ways of defining and applying invariants to practical problem solving are testimony to the fundamental importance of the study of invariants to machine vision. This book represents a snapshot of current research around the world. A version of this collection of papers has appeared in the International Journal of Pattern Recognition and Artificial Intelligence (December 1999). The papers in this book are extended versions of the original material published in the journal. They are organized into two categories: foundations and applications. Foundation papers present new ways of defining or analyzing invariants, and application papers present novel ways in which known invariant theory is extended and effectively applied to real-world problems in interesting and difficult contexts. Each category contains roughly half of the papers, but there is considerable overlap. All papers carry an element of novelty and generalization that will be useful to theoreticians and practitioners alike. It is hoped that this volume will be not only useful but also inspirational to researchers in image processing, pattern recognition and computer vision at large.
Book Synopsis Invariants For Pattern Recognition And Classification by : Marcos A Rodrigues
Download or read book Invariants For Pattern Recognition And Classification written by Marcos A Rodrigues and published by World Scientific. This book was released on 2000-12-29 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was conceived from the realization that there was a need to update recent work on invariants in a single volume providing a useful set of references and pointers to related work. Since the publication in 1992 of J L Mundy and A Zisserman's Geometric Invariance in Computer Vision, the subject has been evolving rapidly. New approaches to invariants have been proposed and novel ways of defining and applying invariants to practical problem solving are testimony to the fundamental importance of the study of invariants to machine vision. This book represents a snapshot of current research around the world.A version of this collection of papers has appeared in the International Journal of Pattern Recognition and Artificial Intelligence (December 1999). The papers in this book are extended versions of the original material published in the journal. They are organized into two categories: foundations and applications. Foundation papers present new ways of defining or analyzing invariants, and application papers present novel ways in which known invariant theory is extended and effectively applied to real-world problems in interesting and difficult contexts. Each category contains roughly half of the papers, but there is considerable overlap. All papers carry an element of novelty and generalization that will be useful to theoreticians and practitioners alike. It is hoped that this volume will be not only useful but also inspirational to researchers in image processing, pattern recognition and computer vision at large.
Book Synopsis Generalized Automated Pattern Recognition by : Michael J. Hannah
Download or read book Generalized Automated Pattern Recognition written by Michael J. Hannah and published by . This book was released on 1971 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Moments and Moment Invariants in Pattern Recognition by : Jan Flusser
Download or read book Moments and Moment Invariants in Pattern Recognition written by Jan Flusser and published by Wiley. This book was released on 2009-11-04 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Special issue Invariants for pattern recognition and classification by : M. A. Rodrigues
Download or read book Special issue Invariants for pattern recognition and classification written by M. A. Rodrigues and published by . This book was released on 1999 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Investigation of Moment Invariants for Pattern Recognition by : Ravi Kumar Chanana
Download or read book Investigation of Moment Invariants for Pattern Recognition written by Ravi Kumar Chanana and published by . This book was released on 1984 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition for Feature-Based and Comparative Visualization by : Michael Schlemmer
Download or read book Pattern Recognition for Feature-Based and Comparative Visualization written by Michael Schlemmer and published by Sudwestdeutscher Verlag Fur Hochschulschriften AG. This book was released on 2011 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition is widely spread as a basis for classification purposes. However, the common pattern recognition and classification methods are usually used on non-spatially-correlated data. For example, moment invariants are a very basic and popular tool for this purpose. Such methods cannot be easily applied on flow data, like wind streams and water flows, magma flows, blood flows for medical purposes, air flow simulations for the design of cars and airplanes. For this reason, this book explains how classic moment invariants have been transformed to facilitate pattern recognition on flow data. The properties of the "Flow Moment Invariants" are analyzed and used to perform Feature-based and Comparative Visualization of flow data.
Book Synopsis Moments and Moment Invariants in Pattern Recognition by : Jan Flusser
Download or read book Moments and Moment Invariants in Pattern Recognition written by Jan Flusser and published by John Wiley & Sons. This book was released on 2009-11-04 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Supervised and Unsupervised Pattern Recognition by : Evangelia Miche Tzanakou
Download or read book Supervised and Unsupervised Pattern Recognition written by Evangelia Miche Tzanakou and published by CRC Press. This book was released on 2017-12-19 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.
Book Synopsis Handbook of Pattern Recognition and Computer Vision by : Chi-hau Chen
Download or read book Handbook of Pattern Recognition and Computer Vision written by Chi-hau Chen and published by World Scientific. This book was released on 2010 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both pattern recognition and computer vision have experienced rapid progress in the last twenty-five years. This book provides the latest advances on pattern recognition and computer vision along with their many applications. It features articles written by renowned leaders in the field while topics are presented in readable form to a wide range of readers. The book is divided into five parts: basic methods in pattern recognition, basic methods in computer vision and image processing, recognition applications, life science and human identification, and systems and technology. There are eight new chapters on the latest developments in life sciences using pattern recognition as well as two new chapters on pattern recognition in remote sensing.
Book Synopsis Orthogonal Image Moments for Human-Centric Visual Pattern Recognition by : S. M. Mahbubur Rahman
Download or read book Orthogonal Image Moments for Human-Centric Visual Pattern Recognition written by S. M. Mahbubur Rahman and published by Springer Nature. This book was released on 2019-10-11 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Variable Illumination and Invariant Features for Detecting and Classifying Varnish Defects by : Ana Pérez Grassi
Download or read book Variable Illumination and Invariant Features for Detecting and Classifying Varnish Defects written by Ana Pérez Grassi and published by KIT Scientific Publishing. This book was released on 2014-08-14 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents a method to detect and classify varnish defects on wood surfaces. Since these defects are only partially visible under certain illumination directions, one image doesn't provide enough information for a recognition task. A classification requires inspecting the surface under different illumination directions, which results in image series. The information is distributed along this series and can be extracted by merging the knowledge about the defect shape and light direction.
Book Synopsis An Evaluation of Moment Invariants as Features for Pattern Classification by : Robert D. Lyon
Download or read book An Evaluation of Moment Invariants as Features for Pattern Classification written by Robert D. Lyon and published by . This book was released on 1994 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Pattern Recognition and Computer Vision by : C. H. Chen
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Book Synopsis Pattern Recognition by : Jürgen Beyerer
Download or read book Pattern Recognition written by Jürgen Beyerer and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-04-01 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features, their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book is to clarifies the concepts so that the reader can easily understand the underlying ideas and the rationale behind the methods. For this purpose, the mathematical treatment of Pattern Recognition is pushed so far that the mechanisms of action become clear and visible, but not farther. Therefore, not all derivations are driven into the last mathematical detail, as a mathematician would expect it. Ideas of proofs are presented instead of complete proofs. From the authors’ point of view, this concept allows to teach the essential ideas of Pattern Recognition with sufficient depth within a relatively lean book. Mathematical methods explained thoroughly. Extremely practical approach with many examples. Based on over ten years lecture at Karlsruhe Institute of Technology. For students but also for practitioners.
Book Synopsis Introduction To Pattern Recognition And Machine Learning by : M Narasimha Murty
Download or read book Introduction To Pattern Recognition And Machine Learning written by M Narasimha Murty and published by World Scientific. This book was released on 2015-04-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter.
Book Synopsis Pattern Recognition and Classification by : Geoff Dougherty
Download or read book Pattern Recognition and Classification written by Geoff Dougherty and published by Springer. This book was released on 2012-10-29 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.
