Watershed-based Image Segmentation for Gray-scale and Color Images PDF Download
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Author: Sergio E. Hernández
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 132
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Book Description
Author: Sergio E. Hernández
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 132
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Book Description
Author: Mahalingam Sundhararajan
Publisher: European Alliance for Innovation
ISBN: 1631903063
Category : Computers
Languages : en
Pages : 1318
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Book Description
I3CAC provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss not only the most recent innovations, trends, and concerns but also practical challenges encountered and solutions adopted in the fields of computing, communication and control systems. Participation of three renowned speakers and oral presentations of the 128 authors were presented in our conference. We strongly believe that the I3CAC 2021 conference provides a good forum for all researchers, developers and practitioners to discuss.
Author: Tao Lei
Publisher: John Wiley & Sons
ISBN: 111985900X
Category : Technology & Engineering
Languages : en
Pages : 340
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Book Description
Image Segmentation Summarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field The process of image segmentation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed. Image segmentation has wide applications in numerous fields ranging from industry detection and bio-medicine to intelligent transportation and architecture. Image Segmentation: Principles, Techniques, and Applications is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authors—such as convolutional neural networks, graph convolutional networks, deformable convolution, and model compression—to assist graduate students and researchers apply and improve image segmentation in their work. Describes basic principles of image segmentation and related mathematical methods such as clustering, neural networks, and mathematical morphology. Introduces new methods for achieving rapid and accurate image segmentation based on classic image processing and machine learning theory. Presents techniques for improved convolutional neural networks for scene segmentation, object recognition, and change detection, etc. Highlights the effect of image segmentation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc. Image Segmentation: Principles, Techniques, and Applications is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods.
Author: John Goutsias
Publisher: Springer Science & Business Media
ISBN: 0792378628
Category : Technology & Engineering
Languages : en
Pages : 453
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Book Description
Mathematical morphology is a powerful methodology for the processing and analysis of geometric structure in signals and images. This book contains the proceedings of the fifth International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing, held June 26-28, 2000, at Xerox PARC, Palo Alto, California. It provides a broad sampling of the most recent theoretical and practical developments of mathematical morphology and its applications to image and signal processing. Areas covered include: decomposition of structuring functions and morphological operators, morphological discretization, filtering, connectivity and connected operators, morphological shape analysis and interpolation, texture analysis, morphological segmentation, morphological multiresolution techniques and scale-spaces, and morphological algorithms and applications. Audience: The subject matter of this volume will be of interest to electrical engineers, computer scientists, and mathematicians whose research work is focused on the theoretical and practical aspects of nonlinear signal and image processing. It will also be of interest to those working in computer vision, applied mathematics, and computer graphics.
Author: Carlos Cruz Corona
Publisher: Springer
ISBN: 3319623591
Category : Technology & Engineering
Languages : en
Pages : 360
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Book Description
This book offers a timely snapshot of soft computing methodologies and their applications to various problems related to sustainability, including electric energy consumption; fault diagnosis; vessel fuel consumption; determining the best sites for new malls; maritime port projects; and ad-hoc vehicular networks. Further, it demonstrates how metaheuristics and machine learning methods, fuzzy linear programming, neural networks, computing with words, linguistic models and other soft computing methods can be efficiently used to solve real-world problems. Intended as a practice-oriented guide for students, researchers, and professionals working at the interface between computer science, industrial engineering, naval engineering, agriculture, and sustainable development / climate change research, it provides readers with a set of intelligent solutions, helping them answer a range of emerging questions related to sustainability.
Author: Lipo Wang
Publisher: Springer
ISBN: 3540318305
Category : Computers
Languages : en
Pages : 1374
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Book Description
This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.
Author: Fouad Sabry
Publisher: One Billion Knowledgeable
ISBN:
Category : Computers
Languages : en
Pages : 136
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Book Description
What is Image Segmentation In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Image segmentation Chapter 2: Edge detection Chapter 3: Scale-invariant feature transform Chapter 4: Thresholding (image processing) Chapter 5: Otsu's method Chapter 6: Corner detection Chapter 7: Graph cuts in computer vision Chapter 8: Mean shift Chapter 9: Range segmentation Chapter 10: Watershed (image processing) (II) Answering the public top questions about image segmentation. (III) Real world examples for the usage of image segmentation in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Image Segmentation.
Author: Francisco Javier Escobar Cañamaque
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Srecko Brlek
Publisher: Springer
ISBN: 3642043976
Category : Computers
Languages : en
Pages : 551
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Book Description
This book constitutes the refereed proceedings of the 15th IAPR International Conference on Discrete Geometry for Computer Imagery, DGCI 2009, held in Montréal, Canada, in September/October 2009. The 42 revised full papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on discrete shape, representation, recognition and analysis; discrete and combinatorial tools for image segmentation and analysis; discrete and combinatorial Topology; models for discrete geometry; geometric transforms; and discrete tomography.
Author: Yu-Jin Zhang
Publisher: CRC Press
ISBN: 1000689425
Category : Computers
Languages : en
Pages : 363
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Book Description
This book focuses on seven commonly used image analysis techniques. It covers aspects from basic principles and practical methods, to new advancement of each selected technique to help readers solve image‐processing related problems in real-life situations. The selected techniques include image segmentation, segmentation evaluation and comparison, saliency object detection, motion analysis, mathematical morphology methods, face recognition and expression classification. The author offers readers a three‐step strategy toward problem‐solving: first, essential principles; then, a detailed explanation; and finally, a discussion on practical and working techniques for specific tasks. He also encourages readers to make full use of available materials from the latest developments and trends. This is an excellent book for those who do not have a complete foundation in image technology but need to use image analysis techniques to perform specific tasks in particular applications.
