Fuzzy Techniques In Image Processing

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Fuzzy Techniques in Image Processing

Author : Etienne E. Kerre
Publisher : Physica
ISBN 13 : 379081847X
Total Pages : 425 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Fuzzy Techniques in Image Processing by : Etienne E. Kerre

Download or read book Fuzzy Techniques in Image Processing written by Etienne E. Kerre and published by Physica. This book was released on 2013-03-19 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since time immemorial, vision in general and images in particular have played an important and essential role in human life. Nowadays, the field of image processing also has numerous scientific, commercial, industrial and military applications. All these applications result from the interaction between fun damental scientific research on the one hand, and the development of new and high-standard technology on the other hand. Regarding the scientific com ponent, quite recently the scientific community became familiar with "fuzzy techniques" in image processing, which make use of the framework of fuzzy sets and related theories. The theory of fuzzy sets was initiated in 1965 by Zadeh, and is one of the most developed models to treat imprecision and uncertainty. Instead of the classical approach that an object belongs or does not belong to a set, the concept of a fuzzy set allows a gradual transition from membership to nonmembership, providing partial degrees of member ship. Fuzzy techniques are often complementary to existing techniques and can contribute to the development of better and more robust methods, as has already been illustrated in numerous scientific branches. With this vol ume, we want to demonstrate that the introduction and application of fuzzy techniques can also be very successful in the area of image processing. This book contains high-quality contributions of over 30 field experts, covering a wide range of both theoretical and practical applications of fuzzy techniques in image processing.

Fuzzy Filters for Image Processing

Author : Mike Nachtegael
Publisher : Springer
ISBN 13 : 354036420X
Total Pages : 393 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Fuzzy Filters for Image Processing by : Mike Nachtegael

Download or read book Fuzzy Filters for Image Processing written by Mike Nachtegael and published by Springer. This book was released on 2013-06-05 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ongoing increase in scale of integration of electronics makes storage and computational power affordable to many applications. Also image process ing systems can benefit from this trend. A variety of algorithms for image processing tasks becomes close at hand. From the whole range of possible approaches, those based on fuzzy logic are the ones this book focusses on. A particular useful property of fuzzy logic techniques is their ability to represent knowledge in a way which is comprehensible to human interpretation. The theory of fuzzy sets and fuzzy logic was initiated in 1965 by Zadeh, and is one of the most developed models to treat imprecision and uncertainty. Instead of the classical approach that an object belongs or does not belong to a set, the concept of a fuzzy set allows a gradual transition from mem bership to nonmembership, providing partial degrees of membership. Fuzzy techniques are often complementary to existing techniques and can contribute to the development of better and more robust methods, as has already been illustrated in numerous scientific branches. The present book resulted from the workshop "Fuzzy Filters for Image Processing" which was organized at the 10th FUZZ-IEEE Conference in Mel bourne, Australia. At this event several speakers have given an overview of the current state-of-the-art of fuzzy filters for image processing. Afterwards, the book has been completed with contributions of other international re searchers.

Fuzzy Logic for Image Processing

Author : Laura Caponetti
Publisher : Springer
ISBN 13 : 3319441302
Total Pages : 138 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Fuzzy Logic for Image Processing by : Laura Caponetti

Download or read book Fuzzy Logic for Image Processing written by Laura Caponetti and published by Springer. This book was released on 2016-09-16 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to fuzzy logic approaches useful in image processing. The authors start by introducing image processing tasks of low and medium level such as thresholding, enhancement, edge detection, morphological filters, and segmentation and shows how fuzzy logic approaches apply. The book is divided into two parts. The first includes vagueness and ambiguity in digital images, fuzzy image processing, fuzzy rule based systems, and fuzzy clustering. The second part includes applications to image processing, image thresholding, color contrast enhancement, edge detection, morphological analysis, and image segmentation. Throughout, they describe image processing algorithms based on fuzzy logic under methodological aspects in addition to applicative aspects. Implementations in java are provided for the various applications.

Fuzzy Image Processing and Applications with MATLAB

Author : Tamalika Chaira
Publisher : CRC Press
ISBN 13 : 1351834215
Total Pages : 237 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Fuzzy Image Processing and Applications with MATLAB by : Tamalika Chaira

Download or read book Fuzzy Image Processing and Applications with MATLAB written by Tamalika Chaira and published by CRC Press. This book was released on 2017-12-19 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: In contrast to classical image analysis methods that employ "crisp" mathematics, fuzzy set techniques provide an elegant foundation and a set of rich methodologies for diverse image-processing tasks. However, a solid understanding of fuzzy processing requires a firm grasp of essential principles and background knowledge. Fuzzy Image Processing and Applications with MATLAB® presents the integral science and essential mathematics behind this exciting and dynamic branch of image processing, which is becoming increasingly important to applications in areas such as remote sensing, medical imaging, and video surveillance, to name a few. Many texts cover the use of crisp sets, but this book stands apart by exploring the explosion of interest and significant growth in fuzzy set image processing. The distinguished authors clearly lay out theoretical concepts and applications of fuzzy set theory and their impact on areas such as enhancement, segmentation, filtering, edge detection, content-based image retrieval, pattern recognition, and clustering. They describe all components of fuzzy, detailing preprocessing, threshold detection, and match-based segmentation. Minimize Processing Errors Using Dynamic Fuzzy Set Theory This book serves as a primer on MATLAB and demonstrates how to implement it in fuzzy image processing methods. It illustrates how the code can be used to improve calculations that help prevent or deal with imprecision—whether it is in the grey level of the image, geometry of an object, definition of an object’s edges or boundaries, or in knowledge representation, object recognition, or image interpretation. The text addresses these considerations by applying fuzzy set theory to image thresholding, segmentation, edge detection, enhancement, clustering, color retrieval, clustering in pattern recognition, and other image processing operations. Highlighting key ideas, the authors present the experimental results of their own new fuzzy approaches and those suggested by different authors, offering data and insights that will be useful to teachers, scientists, and engineers, among others.

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

Author : James C. Bezdek
Publisher : Springer Science & Business Media
ISBN 13 : 0387245790
Total Pages : 786 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Fuzzy Models and Algorithms for Pattern Recognition and Image Processing by : James C. Bezdek

Download or read book Fuzzy Models and Algorithms for Pattern Recognition and Image Processing written by James C. Bezdek and published by Springer Science & Business Media. This book was released on 2006-09-28 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Unique to this volume in the Kluwer Handbooks of Fuzzy Sets Series is the fact that this book was written in its entirety by its four authors. A single notation, presentation style, and purpose are used throughout. The result is an extensive unified treatment of many fuzzy models for pattern recognition. The main topics are clustering and classifier design, with extensive material on feature analysis relational clustering, image processing and computer vision. Also included are numerous figures, images and numerical examples that illustrate the use of various models involving applications in medicine, character and word recognition, remote sensing, military image analysis, and industrial engineering.

Medical Image Processing

Author : Tamalika Chaira
Publisher : CRC Press
ISBN 13 : 1498700470
Total Pages : 236 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Medical Image Processing by : Tamalika Chaira

Download or read book Medical Image Processing written by Tamalika Chaira and published by CRC Press. This book was released on 2015-01-28 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical image analysis using advanced fuzzy set theoretic techniques is an exciting and dynamic branch of image processing. Since the introduction of fuzzy set theory, there has been an explosion of interest in advanced fuzzy set theories—such as intuitionistic fuzzy and Type II fuzzy set—that represent uncertainty in a better way. Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques deals with the application of intuitionistic fuzzy and Type II fuzzy set theories for medical image analysis. Designed for graduate and doctorate students, this higher-level text: Provides a brief introduction to advanced fuzzy set theory, fuzzy/intuitionistic fuzzy aggregation operators, and distance/similarity measures Covers medical image enhancement using advanced fuzzy sets, including MATLAB®-based examples to increase contrast of the images Describes intuitionistic fuzzy and Type II fuzzy thresholding techniques that separate different regions/leukocyte types/abnormal lesions Demonstrates the clustering of unwanted lesions/regions even in the presence of noise by applying intuitionistic fuzzy clustering Highlights the edges of poorly illuminated images and uses intuitionistic fuzzy edge detection to find the edges of different regions Defines fuzzy mathematical morphology and explores its application using the Lukasiewicz operator, t-norms, and t-conorms Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques is useful not only for students, but also for teachers, engineers, scientists, and those interested in the field of medical image analysis. A basic knowledge of fuzzy set is required, along with a solid understanding of mathematics and image processing.

Soft Computing in Image Processing

Author : Mike Nachtegael
Publisher : Springer
ISBN 13 : 354038233X
Total Pages : 487 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Soft Computing in Image Processing by : Mike Nachtegael

Download or read book Soft Computing in Image Processing written by Mike Nachtegael and published by Springer. This book was released on 2007-06-24 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Images have always been very important in human life. Their applications range from primitive communication between humans of all ages to advanced technologies in the industrial, medical and military field. The increased possibilities to capture and analyze images have contributed to the largeness that the scientific field of "image processing" has become today. Many techniques are being applied, including soft computing. "Soft Computing in Image Processing: Recent Advances" follows the edited volumes "Fuzzy Techniques in Image Processing" (volume 52, published in 2000) and "Fuzzy Filters for Image Processing" (volume 122, published in 2003), and covers a wide range of both practical and theoretical applications of soft computing in image processing. The 16 excellent chapters of the book have been grouped into five parts: Applications in Remote Sensing, Applications in Image Retrieval, Applications in Image Analysis, Other Applications, and Theoretical Contributions. The focus of the book is on practical applications, which makes it interesting for every researcher that is involved with soft computing, image processing, or both scientific branches.

Soft Computing for Image Processing

Author : Sankar K. Pal
Publisher : Physica
ISBN 13 : 3790818585
Total Pages : 600 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Soft Computing for Image Processing by : Sankar K. Pal

Download or read book Soft Computing for Image Processing written by Sankar K. Pal and published by Physica. This book was released on 2013-03-19 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of images is no exception to this rule. In the classical image analysis paradigm, the first step is nearly always some sort of segmentation process in which the image is divided into (hopefully, meaningful) parts. It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image. It was also realized very early that many basic properties of and operations on image subsets could be extended to fuzzy subsets; for example, the classic paper on fuzzy sets by Zadeh [2] discussed the "set algebra" of fuzzy sets (using sup for union and inf for intersection), and extended the defmition of convexity to fuzzy sets. These and similar ideas allowed many of the methods of image analysis to be generalized to fuzzy image parts. For are cent review on geometric description of fuzzy sets see, e. g. , [3]. Fuzzy methods are also valuable in image processing and coding, where learning processes can be important in choosing the parameters of filters, quantizers, etc.

Fuzzy Sets Methods in Image Processing and Understanding

Author : Isabelle Bloch
Publisher : Springer Nature
ISBN 13 : 303119425X
Total Pages : 311 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Fuzzy Sets Methods in Image Processing and Understanding by : Isabelle Bloch

Download or read book Fuzzy Sets Methods in Image Processing and Understanding written by Isabelle Bloch and published by Springer Nature. This book was released on 2023-01-01 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of recent methods using higher level information (object or scene level) for advanced tasks such as image understanding along with their applications to medical images. Advanced methods for fuzzy image processing and understanding are presented, including fuzzy spatial objects, geometry and topology, mathematical morphology, machine learning, verbal descriptions of image content, fusion, spatial relations, and structural representations. For each methodological aspect covered, illustrations from the medical imaging domain are provided. This is an ideal book for graduate students and researchers in the field of medical image processing.

Advanced Image Processing Techniques and Applications

Author : Kumar, N. Suresh
Publisher : IGI Global
ISBN 13 : 1522520546
Total Pages : 439 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Advanced Image Processing Techniques and Applications by : Kumar, N. Suresh

Download or read book Advanced Image Processing Techniques and Applications written by Kumar, N. Suresh and published by IGI Global. This book was released on 2017-02-10 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, the scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Advanced Image Processing Techniques and Applications is an essential reference publication for the latest research on digital image processing advancements. Featuring expansive coverage on a broad range of topics and perspectives, such as image and video steganography, pattern recognition, and artificial vision, this publication is ideally designed for scientists, professionals, researchers, and academicians seeking current research on solutions for new challenges in image processing.

Fuzzy Transforms for Image Processing and Data Analysis

Author : Ferdinando Di Martino
Publisher : Springer Nature
ISBN 13 : 3030446131
Total Pages : 220 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Fuzzy Transforms for Image Processing and Data Analysis by : Ferdinando Di Martino

Download or read book Fuzzy Transforms for Image Processing and Data Analysis written by Ferdinando Di Martino and published by Springer Nature. This book was released on 2020-04-22 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book analyzes techniques that use the direct and inverse fuzzy transform for image processing and data analysis. The book is divided into two parts, the first of which describes methods and techniques that use the bi-dimensional fuzzy transform method in image analysis. In turn, the second describes approaches that use the multidimensional fuzzy transform method in data analysis. An F-transform in one variable is defined as an operator which transforms a continuous function f on the real interval [a,b] in an n-dimensional vector by using n-assigned fuzzy sets A1, ... , An which constitute a fuzzy partition of [a,b]. Then, an inverse F-transform is defined in order to convert the n-dimensional vector output in a continuous function that equals f up to an arbitrary quantity ε. We may limit this concept to the finite case by defining the discrete F-transform of a function f in one variable, even if it is not known a priori. A simple extension of this concept to functions in two variables allows it to be used for the coding/decoding and processing of images. Moreover, an extended version with multidimensional functions can be used to address a host of topics in data analysis, including the analysis of large and very large datasets. Over the past decade, many researchers have proposed applications of fuzzy transform techniques for various image processing topics, such as image coding/decoding, image reduction, image segmentation, image watermarking and image fusion; and for such data analysis problems as regression analysis, classification, association rule extraction, time series analysis, forecasting, and spatial data analysis. The robustness, ease of use, and low computational complexity of fuzzy transforms make them a powerful fuzzy approximation tool suitable for many computer science applications. This book presents methods and techniques based on the use of fuzzy transforms in various applications of image processing and data analysis, including image segmentation, image tamper detection, forecasting, and classification, highlighting the benefits they offer compared with traditional methods. Emphasis is placed on applications of fuzzy transforms to innovative problems, such as massive data mining, and image and video security in social networks based on the application of advanced fragile watermarking systems. This book is aimed at researchers, students, computer scientists and IT developers to acquire the knowledge and skills necessary to apply and implement fuzzy transforms-based techniques in image and data analysis applications.

Fuzzy Cluster Analysis

Author : Frank Höppner
Publisher : John Wiley & Sons
ISBN 13 : 9780471988649
Total Pages : 308 pages
Book Rating : 4.9/5 (886 download)

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Book Synopsis Fuzzy Cluster Analysis by : Frank Höppner

Download or read book Fuzzy Cluster Analysis written by Frank Höppner and published by John Wiley & Sons. This book was released on 1999-07-09 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dieser Band konzentriert sich auf Konzepte, Algorithmen und Anwendungen des Fuzzy Clustering. In sich geschlossen werden Techniken wie das Fuzzy-c-Mittel und die Gustafson-Kessel- und Gath- und Gava-Algorithmen behandelt, wobei vom Leser keine Vorkenntnisse auf dem Gebiet von Fuzzy-Systemen erwartet werden. Durch anschauliche Anwendungsbeispiele eignet sich das Buch als Einführung für Praktiker der Datenanalyse, der Bilderkennung und der angewandten Mathematik. (05/99)

Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

Author : Anil Kumar
Publisher : CRC Press
ISBN 13 : 1000091546
Total Pages : 177 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification by : Anil Kumar

Download or read book Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification written by Anil Kumar and published by CRC Press. This book was released on 2020-07-19 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.

Fuzzy Systems in Bioinformatics and Computational Biology

Author : Yaochu Jin
Publisher : Springer Science & Business Media
ISBN 13 : 3540899677
Total Pages : 336 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Fuzzy Systems in Bioinformatics and Computational Biology by : Yaochu Jin

Download or read book Fuzzy Systems in Bioinformatics and Computational Biology written by Yaochu Jin and published by Springer Science & Business Media. This book was released on 2009-04-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties. Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and analysis approaches are also becoming popular in analyzing biological data and modeling biological systems. Numerous research and application results have been reported that demonstrated the effectiveness of fuzzy logic in solving a wide range of biological problems found in bioinformatics, biomedical engineering, and computational biology. Contributed by leading experts world-wide, this edited book contains 16 chapters presenting representative research results on the application of fuzzy systems to genome sequence assembly, gene expression analysis, promoter analysis, cis-regulation logic analysis and synthesis, reconstruction of genetic and cellular networks, as well as biomedical problems, such as medical image processing, electrocardiogram data classification and anesthesia monitoring and control. This volume is a valuable reference for researchers, practitioners, as well as graduate students working in the field of bioinformatics, biomedical engineering and computational biology.

Image Processing

Author : Tinku Acharya
Publisher : John Wiley & Sons
ISBN 13 : 0471745782
Total Pages : 454 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Image Processing by : Tinku Acharya

Download or read book Image Processing written by Tinku Acharya and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.

New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing

Author : Leszek Rutkowski
Publisher : Springer
ISBN 13 : 354040046X
Total Pages : 376 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing by : Leszek Rutkowski

Download or read book New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing written by Leszek Rutkowski and published by Springer. This book was released on 2013-03-09 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Science has made great progress in the twentieth century, with the establishment of proper disciplines in the fields of physics, computer science, molecular biology, and many others. At the same time, there have also emerged many engineering ideas that are interdisciplinary in nature, beyond the realm of such orthodox disciplines. These in clude, for example, artificial intelligence, fuzzy logic, artificial neural networks, evolutional computation, data mining, and so on. In or der to generate new technology that is truly human-friendly in the twenty-first century, integration of various methods beyond specific disciplines is required. Soft computing is a key concept for the creation of such human friendly technology in our modern information society. Professor Rutkowski is a pioneer in this field, having devoted himself for many years to publishing a large variety of original work. The present vol ume, based mostly on his own work, is a milestone in the devel opment of soft computing, integrating various disciplines from the fields of information science and engineering. The book consists of three parts, the first of which is devoted to probabilistic neural net works. Neural excitation is stochastic, so it is natural to investi gate the Bayesian properties of connectionist structures developed by Professor Rutkowski. This new approach has proven to be par ticularly useful for handling regression and classification problems vi Preface in time-varying environments. Throughout this book, major themes are selected from theoretical subjects that are tightly connected with challenging applications.

Image Processing and Pattern Recognition

Author : Frank Y. Shih
Publisher : John Wiley & Sons
ISBN 13 : 0470404612
Total Pages : 564 pages
Book Rating : 4.4/5 (74 download)

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Book Synopsis Image Processing and Pattern Recognition by : Frank Y. Shih

Download or read book Image Processing and Pattern Recognition written by Frank Y. Shih and published by John Wiley & Sons. This book was released on 2010-05-03 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.