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Author : Edward R. Dougherty
Publisher : SPIE Press
Page : 294 pages
File Size : 36,45 MB
Release : 2003
Category : Computers
ISBN : 9780819447203
Morphological image processing, a standard part of the imaging scientist's toolbox, can be applied to a wide range of industrial applications. Concentrating on applications, this text shows how to analyse the problems and then develop successful algorithms to solve them.
Author : Edward R. Dougherty
Publisher : SPIE-International Society for Optical Engineering
Page : 184 pages
File Size : 20,28 MB
Release : 1992
Category : Computers
ISBN :
Binary erosion and dilation. Binary opening and closing. Morphological processing of binary images. Hit-or-miss transform. Granulometries. Gray-scale morphology. Gray-scale morphological algorithms.
Author : Sandipan Dey
Publisher : Packt Publishing Ltd
Page : 483 pages
File Size : 48,31 MB
Release : 2018-11-30
Category : Computers
ISBN : 178934185X
Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.
Author : Pierre Soille
Publisher : Springer Science & Business Media
Page : 322 pages
File Size : 37,99 MB
Release : 2013-03-14
Category : Science
ISBN : 3662039397
The book is self-contained in the sense that it is accessible to engineers, scientists, and practitioners having no prior experience with morphology. In addition, most necessary background notions about digital image processing are covered. The emphasis being put on the techniques useful for solving practical problems rather than the theory underlying mathematical morphology, no special knowledge about set theory and topology is required. Nevertheless, the book goes well beyond an introduction to mathematical morphology. Indeed, starting from the fundamental transformations, more elaborate methods which have proven their practical usefulness are explained. This is achieved through a step by step process pursued until the most recent advances.
Author : Bernhard Burgeth
Publisher : Springer
Page : 19 pages
File Size : 18,6 MB
Release : 2019-06-19
Category : Computers
ISBN : 3030208672
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.
Author : Frank Y. Shih
Publisher : CRC Press
Page : 442 pages
File Size : 35,73 MB
Release : 2017-07-12
Category : Technology & Engineering
ISBN : 1420089447
In the development of digital multimedia, the importance and impact of image processing and mathematical morphology are well documented in areas ranging from automated vision detection and inspection to object recognition, image analysis and pattern recognition. Those working in these ever-evolving fields require a solid grasp of basic fundamentals, theory, and related applications—and few books can provide the unique tools for learning contained in this text. Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. This helps readers analyze key principles and architectures and then use the author’s novel ideas on implementation of advanced algorithms to formulate a practical and detailed plan to develop and foster their own ideas. The book: Presents the history and state-of-the-art techniques related to image morphological processing, with numerous practical examples Gives readers a clear tutorial on complex technology and other tools that rely on their intuition for a clear understanding of the subject Includes an updated bibliography and useful graphs and illustrations Examines several new algorithms in great detail so that readers can adapt them to derive their own solution approaches This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Author : Edward Dougherty
Publisher : CRC Press
Page : 552 pages
File Size : 35,79 MB
Release : 2018-10-03
Category : Technology & Engineering
ISBN : 1482277239
Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.
Author : Shaik Shafiulla Basha
Publisher : LAP Lambert Academic Publishing
Page : 112 pages
File Size : 44,5 MB
Release : 2015-11-26
Category :
ISBN : 9783659661860
Morphological Image Processing is an important tool in the Digital Image Processing, since that science can rigorously quantify many aspects of the geometrical structure of the way that agrees with the human intuition and perception. The Morphological Image Processing is based on geometrically altering image structure. Based on four basic operations of Dilation, Erosion, Opening and Closing, one can construct a class of Morphological Image Processing Tool, which can be used in the place of a Linear Image Processing. Whereas the Linear Image Processing sometimes distort the underlying geometric form of an image, but in Morphological image Processing, the information of the image is not lost. The Morphological Image Processing is implemented and successfully tested in Medical Image Analysis: Detection of Tuberculosis, Industrial Automation: Printed circuit board Inspection, etc.
Author : Thomas B. Moeslund
Publisher : Springer Science & Business Media
Page : 228 pages
File Size : 31,43 MB
Release : 2012-01-24
Category : Computers
ISBN : 1447125037
This textbook presents the fundamental concepts and methods for understanding and working with images and video in an unique, easy-to-read style which ensures the material is accessible to a wide audience. Exploring more than just the basics of image processing, the text provides a specific focus on the practical design and implementation of real systems for processing video data. Features: includes more than 100 exercises, as well as C-code snippets of the key algorithms; covers topics on image acquisition, color images, point processing, neighborhood processing, morphology, BLOB analysis, segmentation in video, tracking, geometric transformation, and visual effects; requires only a minimal understanding of mathematics; presents two chapters dedicated to applications; provides a guide to defining suitable values for parameters in video and image processing systems, and to conversion between the RGB color representation and the HIS, HSV and YUV/YCbCr color representations.
Author : Ravishankar Chityala
Publisher : CRC Press
Page : 335 pages
File Size : 48,44 MB
Release : 2020-06-11
Category : Mathematics
ISBN : 0429516525
Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing—one of the first books to integrate these topics together. By improving readers’ knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples. A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The second part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry. Features Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images. Contains many examples, detailed derivations, and working Python examples of the techniques. Offers practical tips on image acquisition and processing. Includes numerous exercises to test the reader’s skills in Python programming and image processing, with solutions to selected problems, example programs, and images available on the book’s web page. New to this edition Machine learning has become an indispensable part of image processing and computer vision, so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks. A new chapter on affine transform and many new algorithms. Updated Python code aligned to the latest version of modules.