Download or read book Image Segmentation and Compression Using the Tree of Shapes of an Image written by Laura Igual Muñoz and published by . This book was released on 2005 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book From Gestalt Theory to Image Analysis written by Agnès Desolneux and published by Springer Science & Business Media. This book was released on 2007-12-24 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a new theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are a mathematical formalization of the Gestalt theory. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The book is mathematically self-contained, needing only basic understanding of probability and calculus. The text includes more than 130 illustrations, and numerous examples based on specific images on which the theory is tested. Detailed exercises at the end of each chapter help the reader develop a firm understanding of the concepts imparted.

Download or read book Sub bit pixel tree coding of images using improved image segmentation written by Steven D. Lunny and published by . This book was released on 1984 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mathematical Morphology and Its Applications to Signal and Image Processing written by Bernhard Burgeth and published by Springer. This book was released on 2019-06-19 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the refereed proceedings of the 14th International Symposium on Mathematical Morphology, ISMM 2019, held in Saarbrücken, Germany, in July 2019. The 40 revised full papers presented together with one invited talk were carefully reviewed and selected from 54 submissions. The papers are organized in topical sections on Theory, Discrete Topology and Tomography, Trees and Hierarchies, Multivariate Morphology, Computational Morphology, Machine Learning, Segmentation, Applications in Engineering, and Applications in (Bio)medical Imaging.

Download or read book Generation and Analysis of Segmentation Trees for Natural Images written by Emre Akbas and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation is about extracting as well as making use of the structure and hierarchy present in images. We develop a new low-level, multiscale, hierarchical image segmentation algorithm designed to detect image regions regardless of their shapes, sizes, and levels of interior homogeneity. We model a region as a connected set of pixels that is surrounded by ramp edge discontinuities where the magnitude of these discontinuities is large compared to the variation inside the region. Each region is associated with a scale depending on the magnitude of the weakest part of its boundary. Traversing through the range of all possible scales, we obtain all regions present in the image. Regions strictly merge as the scale increases; hence a tree is formed where the root node corresponds to the whole image, and nodes close to the root along a path are large, while their children nodes are smaller and capture embedded details. To evaluate the accuracy and precision of our algorithm, as well as to compare it to the existing algorithms, we develop a new benchmark dataset for low-level image segmentation. In this benchmark, small patches of many images are hand-segmented by human subjects. We provide evaluation methods for both boundary-based and region-based performance of algorithms. We show that our proposed algorithm performs better than the existing low-level segmentation algorithms on this benchmark. Next, we investigate the segmentation-based statistics of natural images. Such statistics capture geometric and topological properties of images, which is not possible to obtain using pixel-, patch-, or subband-based methods. We compile and use segmentation statistics from a large number of images, and propose a Markov random field based model for estimating them. Our estimates confirm some of the previous statistical properties of natural images as well as yield new ones. To demonstrate the value of the statistics, we successfully use them as priors in image classification and semantic image segmentation. We also investigate the importance of different visual cues to describe image regions for solving the region correspondence problem. We design and develop psychophysical experiments to learn the weights of different cues by evaluating their impact on binocular fusibility by human subjects. Using a head-mounted display, we show a set of elliptical regions to one eye and slightly different versions of the same set of regions to the other eye of human subjects. We then ask them whether the ellipses fuse or not. By systematically varying the parameters of the elliptical shapes, and testing for fusion, we learn a perceptual distance function between two elliptical regions. We evaluate this function on ground-truth stereo image pairs. Finally, we propose a novel multiple instance learning (MIL) method. In MIL, in contrast to classical supervised learning, the entities to be classified are called bags, each of which contains an arbitrary number of elements called instances. We propose an additive model for bag classification where we exploit the idea of searching for discriminative instances, which we call prototypes. We show that our bag-classifier can be learned in a boosting framework, leading to an iterative algorithm, which learns prototype-based weak learners that are linearly combined. At each iteration of our proposed method, we search for a new prototype so as to maximally discriminate between the positive and negative bags, which are themselves weighted according to how well they were discriminated in earlier iterations. Unlike previous instance selection based MIL methods, we do not restrict the prototypes to a discrete set of training instances but allow them to take arbitrary values in the instance feature space. We also do not restrict the total number of prototypes and the number of selected-instances per bag; these quantities are completely data-driven. We show that our method outperforms state-of-the-art MIL methods on a number of benchmark datasets. We also apply our method to large-scale image classification, where we show that the automatically selected prototypes map to visually meaningful image regions.

Download or read book Shape in Picture written by Ying-Lie O and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 685 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fields of image analysis, computer vision, and artificial intelligence all make use of descriptions of shape in grey-level images. Most existing algorithms for the automatic recognition and classification of particular shapes have been devel oped for specific purposes, with the result that these methods are often restricted in their application. The use of advanced and theoretically well-founded math ematical methods should lead to the construction of robust shape descriptors having more general application. Shape description can be regarded as a meeting point of vision research, mathematics, computing science, and the application fields of image analy sis, computer vision, and artificial intelligence. The NATO Advanced Research Workshop "Shape in Picture" was organised with a twofold objective: first, it should provide all participants with an overview of relevant developments in these different disciplines; second, it should stimulate researchers to exchange original results and ideas across the boundaries of these disciplines. This book comprises a widely drawn selection of papers presented at the workshop, and many contributions have been revised to reflect further progress in the field. The focus of this collection is on mathematical approaches to the construction of shape descriptions from grey-level images. The book is divided into five parts, each devoted to a different discipline. Each part contains papers that have tutorial sections; these are intended to assist the reader in becoming acquainted with the variety of approaches to the problem.

Download or read book Second International Conference on Image Processing and Capsule Networks written by Joy Iong-Zong Chen and published by Springer Nature. This book was released on 2021-09-09 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications. The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.

Download or read book Intelligent Fractal Based Image Analysis written by Soumya Ranjan Nayak and published by Elsevier. This book was released on 2024-05-27 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis. Intelligent Fractal-Based Image Analysis: Application in Pattern Recognition and Machine Vision provides insights into the current strengths and weaknesses of different applications as well as research findings on fractal graphics in engineering and science applications. The book aims to improve the exchange of ideas and coherence between various core computing methods and highlight the relevance of related application areas for advanced as well as novice-user application. The book presents an in-depth look at core concepts, methodological aspects, and advanced feature opportunities, focusing on major real time applications in engineering science and health science. The book will appeal to researchers, data scientists, industry professionals, and graduate students in the fields of fractal graphics and its related applications. - Investigates advanced fractal theories spanning neural networks, fuzzy logic, machine learning, deep learning, and hybrid intelligent systems in solving pattern recognition problems - Explores the application of fractal theories to a wide range of medical image processing modalities - Presents case studies that illustrate the application and integration of fractal theories into intelligent computing in the resolution of important pattern recognition and machine vision problems

Download or read book Image Segmentation for Object Based Image Compression written by Junaid Ahmed and published by . This book was released on 2000 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advances in Modelling Animation and Rendering written by John Vince and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Advances in computer technology and developments such as the Internet provide a constant momentum to design new techniques and algorithms to support computer graphics. Modelling, animation and rendering remain principal topics in the filed of computer graphics and continue to attract researchers around the world." This volume contains the papers presented at Computer Graphics International 2002, in July, at the University of Bradford, UK. These papers represent original research in computer graphics from around the world and cover areas such as: - Real-time computer animation - Image based rendering - Non photo-realistic rendering - Virtual reality - Avatars - Geometric and solid modelling - Computational geometry - Physically based modelling - Graphics hardware architecture - Data visualisation - Data compression The focus is on the commercial application and industrial use of computer graphics and digital media systems.

Download or read book Geometric Description of Images as Topographic Maps written by Vicent Caselles and published by Springer. This book was released on 2009-12-24 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the basic geometric contents of an image and presents a treedatastructuretohandleite?ciently.Itanalyzesalsosomemorphological operators that simplify this geometric contents and their implementation in termsofthe datastructuresintroduced.It?nallyreviewsseveralapplications to image comparison and registration, to edge and corner computation, and the selection of features associated to a given scale in images. Let us ?rst say that, to avoid a long list, we shall not give references in this summary; they are obviously contained in this monograph. A gray level image is usually modeled as a function de?ned in a bounded N domain D? R (typically N = 2 for usual snapshots, N=3formedical images or movies) with values in R. The sensors of a camera or a CCD array transform the continuum of light energies to a ?nite interval of values by means of a nonlinear function g. The contrast change g depends on the pr- ertiesofthesensors,butalsoontheilluminationconditionsandthere?ection propertiesofthe objects,andthoseconditionsaregenerallyunknown.Images are thus observed modulo an arbitrary and unknown contrast change.

Download or read book Image Based Modeling of Plants and Trees written by Sing Bang Kang and published by Springer Nature. This book was released on 2022-05-31 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plants and trees are among the most complex natural objects. Much work has been done attempting to model them, with varying degrees of success. In this book, we review the various approaches in computer graphics, which we categorize as rule-based, image-based, and sketch-based methods. We describe our approaches for modeling plants and trees using images. Image-based approaches have the distinct advantage that the resulting model inherits the realistic shape and complexity of a real plant or tree. We use different techniques for modeling plants (with relatively large leaves) and trees (with relatively small leaves).With plants, we model each leaf from images, while for trees, the leaves are only approximated due to their small size and large number. Both techniques start with the same initial step of structure from motion on multiple images of the plant or tree that is to be modeled. For our plant modeling system, because we need to model the individual leaves, these leaves need to be segmented out from the images. We designed our plant modeling system to be interactive, automating the process of shape recovery while relying on the user to provide simple hints on segmentation. Segmentation is performed in both image and 3D spaces, allowing the user to easily visualize its effect immediately. Using the segmented image and 3D data, the geometry of each leaf is then automatically recovered from the multiple views by fitting a deformable leaf model. Our system also allows the user to easily reconstruct branches in a similar manner. To model trees, because of the large leaf count, small image footprint, and widespread occlusions, we do not model the leaves exactly as we do for plants. Instead, we populate the tree with leaf replicas from segmented source images to reconstruct the overall tree shape. In addition, we use the shape patterns of visible branches to predict those of obscured branches. As a result, we are able to design our tree modeling system so as to minimize user intervention. We also handle the special case of modeling a tree from only a single image. Here, the user is required to draw strokes on the image to indicate the tree crown (so that the leaf region is approximately known) and to refine the recovery of branches. As before, we concatenate the shape patterns from a library to generate the 3D shape. To substantiate the effectiveness of our systems, we show realistic reconstructions of a variety of plants and trees from images. Finally, we offer our thoughts on improving our systems and on the remaining challenges associated with plant and tree modeling. Table of Contents: Introduction / Review of Plant and Tree Modeling Techniques / Image-Based Technique for Modeling Plants / Image-Based Technique for Modeling Trees / Single Image Tree Modeling / Summary and Concluding Remarks / Acknowledgments

Download or read book Image based Modeling of Plants and Trees written by Sing Bing Kang and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plants and trees are among the most complex natural objects. Much work has been done attempting to model them, with varying degrees of success. In this book, we review the various approaches in computer graphics, which we categorize as rule-based, image-based, and sketch-based methods. We describe our approaches for modeling plants and trees using images. Image-based approaches have the distinct advantage that the resulting model inherits the realistic shape and complexity of a real plant or tree. We use different techniques for modeling plants (with relatively large leaves) and trees (with relatively small leaves).With plants, we model each leaf from images, while for trees, the leaves are only approximated due to their small size and large number. Both techniques start with the same initial step of structure from motion on multiple images of the plant or tree that is to be modeled. For our plant modeling system, because we need to model the individual leaves, these leaves need to be segmented out from the images. We designed our plant modeling system to be interactive, automating the process of shape recovery while relying on the user to provide simple hints on segmentation. Segmentation is performed in both image and 3D spaces, allowing the user to easily visualize its effect immediately. Using the segmented image and 3D data, the geometry of each leaf is then automatically recovered from the multiple views by fitting a deformable leaf model. Our system also allows the user to easily reconstruct branches in a similar manner. To model trees, because of the large leaf count, small image footprint, and widespread occlusions, we do not model the leaves exactly as we do for plants. Instead, we populate the tree with leaf replicas from segmented source images to reconstruct the overall tree shape. In addition, we use the shape patterns of visible branches to predict those of obscured branches. As a result, we are able to design our tree modeling system so as to minimize user intervention. We also handle the special case of modeling a tree from only a single image. Here, the user is required to draw strokes on the image to indicate the tree crown (so that the leaf region is approximately known) and to refine the recovery of branches. As before, we concatenate the shape patterns from a library to generate the 3D shape. To substantiate the effectiveness of our systems, we show realistic reconstructions of a variety of plants and trees from images. Finally, we offer our thoughts on improving our systems and on the remaining challenges associated with plant and tree modeling. Table of Contents: Introduction / Review of Plant and Tree Modeling Techniques / Image-Based Technique for Modeling Plants / Image-Based Technique for Modeling Trees / Single Image Tree Modeling / Summary and Concluding Remarks / Acknowledgments

Download or read book Image Analysis written by Arnt-Borre Salberg and published by Springer Science & Business Media. This book was released on 2009-07-14 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at the Scandinavian Conference on Image Analysis, SCIA 2009, which was held at the Radisson SAS Scandinavian Hotel, Oslo, Norway, June 15–18. SCIA 2009 was the 16th in the biennial series of conferences, which has been organized in turn by the Scandinavian countries Sweden, Finland, D- mark and Norway since 1980. The event itself has always attracted participants and author contributions from outside the Scandinavian countries, making it an international conference. Theconferenceincludedafulldayoftutorialsand?vekeynotetalksprovided by world-renowned experts. The program covered high-quality scienti?c cont- butions within image analysis, human and action analysis, pattern and object recognition,colorimagingandquality,medicalandbiomedicalapplications,face andheadanalysis,computer vision,andmultispectralcoloranalysis. The papers werecarefully selected based on at least two reviews. Among 154 submissions 79 wereaccepted,leadingtoanacceptancerateof51%. SinceSCIAwasarrangedas a single-track event, 30 papers were presented in the oral sessions and 49 papers were presented in the poster sessions. A separate session on multispectral color science was organized in cooperation with the 11th Symposium of Multispectral Color Science (MCS 2009). Since 2009 was proclaimed the “International Year of Astronomy” by the United Nations General Assembly, the conference also contained a session on the topic “Imageand PatternAnalysis in Astronomyand Astrophysics. ” SCIA has a reputation of having a friendly environment, in addition to hi- quality scienti?c contributions. We focused on maintaining this reputation, by designing a technical and social program that we hope the participants found interesting and inspiring for new research ideas and network extensions. We thank the authors for submitting their valuable work to SCIA.

Download or read book Handbook of Image and Video Processing written by Alan C. Bovik and published by Academic Press. This book was released on 2010-07-21 with total page 1429 pages. Available in PDF, EPUB and Kindle. Book excerpt: 55% new material in the latest edition of this "must-have for students and practitioners of image & video processing!This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today's explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader's own potential applications About the Editor... Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.* No other resource for image and video processing contains the same breadth of up-to-date coverage* Each chapter written by one or several of the top experts working in that area* Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various, image-intensive disciplines

Download or read book Handbook of Medical Image Processing and Analysis written by Isaac Bankman and published by Elsevier. This book was released on 2008-12-24 with total page 1009 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Medical Image Processing and Analysis is a comprehensive compilation of concepts and techniques used for processing and analyzing medical images after they have been generated or digitized. The Handbook is organized into six sections that relate to the main functions: enhancement, segmentation, quantification, registration, visualization, and compression, storage and communication.The second edition is extensively revised and updated throughout, reflecting new technology and research, and includes new chapters on: higher order statistics for tissue segmentation; tumor growth modeling in oncological image analysis; analysis of cell nuclear features in fluorescence microscopy images; imaging and communication in medical and public health informatics; and dynamic mammogram retrieval from web-based image libraries.For those looking to explore advanced concepts and access essential information, this second edition of Handbook of Medical Image Processing and Analysis is an invaluable resource. It remains the most complete single volume reference for biomedical engineers, researchers, professionals and those working in medical imaging and medical image processing.Dr. Isaac N. Bankman is the supervisor of a group that specializes on imaging, laser and sensor systems, modeling, algorithms and testing at the Johns Hopkins University Applied Physics Laboratory. He received his BSc degree in Electrical Engineering from Bogazici University, Turkey, in 1977, the MSc degree in Electronics from University of Wales, Britain, in 1979, and a PhD in Biomedical Engineering from the Israel Institute of Technology, Israel, in 1985. He is a member of SPIE. - Includes contributions from internationally renowned authors from leading institutions - NEW! 35 of 56 chapters have been revised and updated. Additionally, five new chapters have been added on important topics incluling Nonlinear 3D Boundary Detection, Adaptive Algorithms for Cancer Cytological Diagnosis, Dynamic Mammogram Retrieval from Web-Based Image Libraries, Imaging and Communication in Health Informatics and Tumor Growth Modeling in Oncological Image Analysis. - Provides a complete collection of algorithms in computer processing of medical images - Contains over 60 pages of stunning, four-color images

Download or read book Computer Vision In Robotics And Industrial Applications written by Dominik Sankowski and published by World Scientific. This book was released on 2014-06-26 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a collection of practical applications of image processing and analysis. Different vision systems are more often used among others in the automotive industry, pharmacy, military and police equipment, automated production and measurement systems. In each of these fields of technology, digital image processing and analysis module is a critical part of the process of building this type of system. The majority of books in the market deal with theoretical issues. However, this unique publication specially highlights industrial applications, especially industrial measurement applications. Along with its wide spectrum of image processing and analysis applications, this book is an interesting reference for both students and professionals.