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Image and Reality: Kekule, Kopp, and the Scientific Imagination
by Alan J. RockeNineteenth-century chemists were faced with a particular problem: how to depict the atoms and molecules that are beyond the direct reach of our bodily senses. In visualizing this microworld, these scientists were the first to move beyond high-level philosophical speculations regarding the unseen. In Image and Reality, Alan Rocke focuses on the community of organic chemists in Germany to provide the basis for a fuller understanding of the nature of scientific creativity. Arguing that visual mental images regularly assisted many of these scientists in thinking through old problems and new possibilities, Rocke uses a variety of sources, including private correspondence, diagrams and illustrations, scientific papers, and public statements, to investigate their ability to not only imagine the invisibly tiny atoms and molecules upon which they operated daily, but to build detailed and empirically based pictures of how all of the atoms in complicated molecules were interconnected. These portrayals of “chemical structures,” both as mental images and as paper tools, gradually became an accepted part of science during these years and are now regarded as one of the central defining features of chemistry. In telling this fascinating story in a manner accessible to the lay reader, Rocke also suggests that imagistic thinking is often at the heart of creative thinking in all fields. Image and Reality is the first book in the Synthesis series, a series in the history of chemistry, broadly construed, edited by Angela N. H. Creager, John E. Lesch, Stuart W. Leslie, Lawrence M. Principe, Alan Rocke, E. C. Spary, and Audra J. Wolfe, in partnership with the Chemical Heritage Foundation.
Image and Signal Processing
by Alamin Mansouri Fathallah Nouboud Alain Chalifour Driss Mammass Jean Meunier Abderrahim ElmoatazThis book constitutes the refereed proceedings of the 7th International Conference, ICISP 2016, held in May/June 2016 in Trois-Rivières, QC, Canada. The 40 revised full papers were carefully reviewed and selected from 83 submissions. The contributions are organized in topical sections on features extraction, computer vision, and pattern recognition; multispectral and color imaging; image filtering, segmentation, and super-resolution; signal processing; biomedical imaging; geoscience and remote sensing; watermarking, authentication and coding; and 3d acquisition, processing, and applications.
Image and Video Color Editing (Synthesis Lectures on Visual Computing: Computer Graphics, Animation, Computational Photography and Imaging)
by Shiguang LiuThis book covers image and video color editing research advances over the last two decades. Bringing readers up to speed on digital image and video editing techniques and research, the book delves into an area that has attracted much attention from researchers due to the rapid development of computer graphics and the widespread prevalence of digital cameras and mobile phones in daily life. Readers will get a comprehensive overview of the theory and application of color transfer, emotional color transfer, colorization, decolorization, and style transfer in altering still and moving digital images. Despite the existence of professional image editing software that can complete complex image editing work, the skills required to achieve satisfactory editing results can be prohibitive, and even professional image editors need to spend a lot of time developing and maintaining aptitude in a niche tool. Instead, the book explores image and video editing techniques that are simple and effective alternatives to such editing software that professional and amateur image editors can utilize. The book focuses on color as one of the most important features of an image or video. Image and video color editing aims to dramatically alter source images suitable for a wide range of applications.
Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards (Second Edition) (Image Processing Series)
by Yun Q. Shi Huifang Sun<p>Multimedia hardware still cannot accommodate the demand for large amounts of visual data. Without the generation of high-quality video bitstreams, limited hardware capabilities will continue to stifle the advancement of multimedia technologies. Thorough grounding in coding is needed so that applications such as MPEG-4 and JPEG 2000 may come to fruition. <p>Image and Video Compression for Multimedia Engineering provides a solid, comprehensive understanding of the fundamentals and algorithms that lead to the creation of new methods for generating high quality video bit streams. The authors present a number of relevant advances along with international standards. <p>Visual data, image, and video coding will continue to enable the creation of advanced hardware, suitable to the demands of new applications. Covering both image and video compression, this book yields a unique, self-contained reference for practitioners tobuild a basis for future study, research, and development.</p>
Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, Third Edition (Image Processing Series)
by Yun-Qing Shi Huifang SunThe latest edition provides a comprehensive foundation for image and video compression. It covers HEVC/H.265 and future video coding activities, in addition to Internet Video Coding. The book features updated chapters and content, along with several new chapters and sections. It adheres to the current international standards, including the JPEG standard.
Image and Video Technology
by Thomas Bräunl Brendan Mccane Mariano Rivera Xinguo YuThisbook constitutes the thoroughly refereed post-conference proceedings of the 7thPacific Rim Symposium on Image and Video Technology, PSIVT 2015, held in Auckland,New Zealand, in November 2015. Thetotal of 61 revised papers was carefully reviewed and selected from 133submissions. The papers are organized in topical sections on color and motion,image/video coding and transmission, computational photography and arts, computervision and applications, image segmentation and classification, videosurveillance, biomedical image processing and analysis, object and patternrecognition, computer vision and pattern recognition, image/video processingand analysis, and pattern recognition.
Image and Video Technology: PSIVT 2017 International Workshops, Wuhan, China, November 20-24, 2017, Revised Selected Papers (Lecture Notes in Computer Science #10799)
by Shin'Ichi SatohThis book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in the framework of the 8th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2017, in Wuhan, China, in November 2017: Workshop on Human Behavior Analysis; Workshop on Educational Cloud and Image/Video Enriched Cloud Services, ECIVECS; Workshop: Vision Meets Graphics, VG; Workshop on Active Electro-Optical Sensors for Aerial and Space Imaging, EO4AS; and Workshop on Computer Vision and Modern Vehicles, CVMV.The 34 revised full papers and 2 posters presented were carefully selected from 103 submissions. The papers cover the full range of state-of-the-art research in image and video technology with topics ranging from well-established areas to novel current trends.
Image and Video Technology: 9th Pacific-Rim Symposium, PSIVT 2019, Sydney, NSW, Australia, November 18–22, 2019, Proceedings (Lecture Notes in Computer Science #11854)
by Zhixun Su Akihiro Sugimoto Chilwoo LeeThis book constitutes the conference proceedings of the 9th Pacific Rim Symposium on Image and Video Technology, PSIVT 2019, held in Sydney, NSW, Australia, in November 2019. A total of 31 papers were carefully reviewed and selected from 55 submissions. The main conference comprises 11 major subject areas that span the field of image and video technology, namely imaging and graphics hardware and visualization, image/video coding and transmission, image/video processing and analysis, image/video retrieval and scene understanding, applications of image and video technology, biomedical image processing and analysis, biometrics and image forensics, computational photography and arts, computer and robot vision, pattern recognition, and video surveillance.
Image and Video Technology - PSIVT 2015 Workshops
by Fay Huang Akihiro SugimotoThis book constitutes the thoroughly refereedpost-conference proceedings of six international workshops held in theframework of the 7th Pacific-Rim Symposium on Image and Video Technology, PSIVT2015, during November 23-24, 2015, in Auckland, New Zealand. The 29 revised full papers presented werecarefully selected from 58 submissions. Their topics diversely ranged fromwell-established areas to novel current trends: robot vision, RV 2015; 2D and3D geometric properties from incomplete data, GPID 2015; vision meets graphics,VG 2015; passive and active electro-optical sensors for aerial and spaceimaging, EO4AS 2015; mathematical and computational methods in biomedicalimaging and image analysis, MCBMIIA 2015; and video surveillance, VSWS 2015.
Image-Based and Fractional-Order Control for Mechatronic Systems: Theory and Applications with MATLAB® (Advances in Industrial Control)
by Clara Mihaela Ionescu Cosmin Copot Cristina I. MuresanThis book unites two fast-developing forms of control—vision-based control and fractional-order control—and applies them in mechatronic systems.Image-Based and Fractional-Order Control for Mechatronic Systems is presented in two parts covering the theory and applications of the subject matter. The theoretical material presents the concepts of visual servoing and image-based feature extraction for feedback loops and fractional-order control. It discusses a range of systems from the classic monocular camera to new RGB-D sensors. The applications part of the book first discusses practical issues with the implementation of fractional-order control, comparing them with more traditional integer-order PID systems. The authors then introduce real-life examples such as a manipulator robot and a Stewart platform and results generated from such systems. MATLAB® functions and source codes are included wherever relevant to help readers develop simulations based on the theoretical ideas and practical examples in the text. Suggestions for the use of other pertinent open-source software are also indicated with the places where such may be obtained. With its combination of theoretical ideas and practical examples, Image-Based and Fractional-Order Control for Mechatronic Systems will be of interest to academic researchers looking to develop the fields of vision-based and fractional-order control and to engineers who are looking for developments that will help them provide closer control of their plants than can be achieved with integer-order PID.Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Image-Based Computational Modeling of the Human Circulatory and Pulmonary Systems
by Krishnan B. Chandran Joseph M. Reinhardt H. S. UdaykumarImage-Based Computational Modeling of the Human Circulatory and Pulmonary Systems provides an overview of the current modeling methods and applications enhancing interventional treatments and computer-aided surgery. A detailed description of the techniques behind image acquisition, processing and three-dimensional reconstruction are included. Techniques for the computational simulation of solid and fluid mechanics and structure interaction are also discussed, in addition to various cardiovascular and pulmonary applications. Engineers and researchers involved with image processing and computational modeling of human organ systems will find this a valuable reference.
Image Based Computing for Food and Health Analytics: IBCFHA
by Rajeev Tiwari Deepika Koundal Shuchi UpadhyayIncrease in consumer awareness of nutritional habits has placed automatic food analysis in the spotlight in recent years. However, food-logging is cumbersome and requires sufficient knowledge of the food item consumed. Additionally, keeping track of every meal can become a tedious task. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to recall foods eaten. Food understanding from digital media has become a challenge with important applications in many different domains. Substantial research has demonstrated that digital imaging accurately estimates dietary intake in many environments and it has many advantages over other methods. However, how to derive the food information effectively and efficiently remains a challenging and open research problem. The provided recommendations could be based on calorie counting, healthy food and specific nutritional composition. In addition, if we also consider a system able to log the food consumed by every individual along time, it could provide health-related recommendations in the long-term. Computer Vision specialists have developed new methods for automatic food intake monitoring and food logging. Fourth Industrial Revolution [4.0 IR] technologies such as deep learning and computer vision robotics are key for sustainable food understanding. The need for AI based technologies that allow tracking of physical activities and nutrition habits are rapidly increasing and automatic analysis of food images plays an important role. Computer vision and image processing offers truly impressive advances to various applications like food analytics and healthcare analytics and can aid patients in keeping track of their calorie count easily by automating the calorie counting process. It can inform the user about the number of calories, proteins, carbohydrates, and other nutrients provided by each meal. The information is provided in real-time and thus proves to be an efficient method of nutrition tracking and can be shared with the dietician over the internet, reducing healthcare costs. This is possible by a system made up of, IoT sensors, Cloud-Fog based servers and mobile applications. These systems can generate data or images which can be analyzed using machine learning algorithms. Image Based Computing for Food and Health Analytics covers the current status of food image analysis and presents computer vision and image processing based solutions to enhance and improve the accuracy of current measurements of dietary intake. Many solutions are presented to improve the accuracy of assessment by analyzing health images, data and food industry based images captured by mobile devices. Key technique innovations based on Artificial Intelligence and deep learning-based food image recognition algorithms are also discussed. This book examines the usage of 4.0 industrial revolution technologies such as computer vision and artificial intelligence in the field of healthcare and food industry, providing a comprehensive understanding of computer vision and intelligence methodologies which tackles the main challenges of food and health processing. Additionally, the text focuses on the employing sustainable 4 IR technologies through which consumers can attain the necessary diet and nutrients and can actively monitor their health. In focusing specifically on the food industry and healthcare analytics, it serves as a single source for multidisciplinary information involving AI and vision techniques in the food and health sector. Current advances such as Industry 4.0 and Fog-Cloud based solutions are covered in full, offering readers a fully rounded view of these rapidly advancing health and food analysis systems.
Image-Based Damage Assessment for Underwater Inspections
by Michael O’Byrne Bidisha Ghosh Franck Schoefs Vikram PakrashiInspection is crucial to the management of ageing infrastructure. Visual information on structures is regularly collected but very little work exists on its organised and quantitative analysis, even though image processing can significantly enhance these inspection processes and transfer real financial and safety benefits to the managers, owners and users. Additionally, new opportunities exist in the fast evolving sectors of wind and wave energy to add value to image-based inspection techniques. <P><P>This book is a first for structural engineers and inspectors who wish to harness the full potential of cameras as an inspection tool. It is particularly directed to the inspection of offshore and marine structures and the application of image-based methods in underwater inspections. It outlines a set of best practice guidelines for obtaining imagery, then the fundamentals of image processing are covered along with several image processing techniques which can be used to assess multiple damage forms: crack detection, corrosion detection, and depth analysis of marine growth on offshore structures. The book provides benchmark performance measures for these techniques under various visibility conditions using an image repository which will help inspectors to envisage the effectiveness of the techniques when applied. MATLAB® scripts and access to the underwater image repository are included so readers can run these techniques themselves. <P><P>Practising engineers and managers of infrastructure assets are guided in image processing based inspection. Researchers can use this book as a primer, and it also suits advanced graduate courses in infrastructure management or on applied image processing.
Image-Based Geometric Modeling and Mesh Generation
by Yongjie Jessica ZhangAs a new interdisciplinary research area, "image-based geometric modeling and mesh generation" integrates image processing, geometric modeling and mesh generation with finite element method (FEM) to solve problems in computational biomedicine, materials sciences and engineering. It is well known that FEM is currently well-developed and efficient, but mesh generation for complex geometries (e.g., the human body) still takes about 80% of the total analysis time and is the major obstacle to reduce the total computation time. It is mainly because none of the traditional approaches is sufficient to effectively construct finite element meshes for arbitrarily complicated domains, and generally a great deal of manual interaction is involved in mesh generation. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications.
Image Co-segmentation (Studies in Computational Intelligence #1082)
by Avik Hati Rajbabu Velmurugan Sayan Banerjee Subhasis ChaudhuriThis book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder–decoder network, meta-learning, conditional variational encoder–decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning.
Image Color Feature Extraction Techniques: Fundamentals and Applications (SpringerBriefs in Applied Sciences and Technology)
by Jyotismita Chaki Nilanjan DeyThis book introduces a range of image color feature extraction techniques. Readers are encouraged to try implementing the techniques discussed here on their own, all of which are presented in a very simple and step-by-step manner. In addition, the book can be used as an introduction to image color feature techniques for those who are new to the research field and software. The techniques are very easy to understand as most of them are described with pictorial examples. Not only the techniques themselves, but also their applications are covered. Accordingly, the book offers a valuable guide to these tools, which are a vital component of content-based image retrieval (CBIR).
Image Content Retargeting: Maintaining Color, Tone, and Spatial Consistency
by Alessandro Artusi Francesco Banterle Tunç Ozan Aydın Daniele Panozzo Olga Sorkine-HornungIn recent years visual devices have proliferated, from the massive high-resolution, high-contrast screens to the tiny ones on mobile phones, with their limited dynamic range and color gamut. The wide variety of screens on which content may be viewed creates a challenge for developers. Adapting visual content for optimized viewing on all devices is called retargeting. This is the first book to provide a holistic view of the subject, thoroughly reviewing and analyzing the many techniques that have been developed for retargeting along dimensions such as color gamut, dynamic range, and spatial resolution.
Image Copy-Move Forgery Detection: New Tools and Techniques (Studies in Computational Intelligence #1017)
by Badal Soni Pradip K. DasThis book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.
Image Encryption: A Communication Perspective
by Osama S. Faragallah El-Sayed M. El-Rabaie Fathi E. Abd El-Samie Hossam Eldin Ahmed Ibrahim F. Elashry Mai H. Shahieen Saleh A. AlshebeiliInvestigating image encryption approaches, this book examines image encryption algorithms for the purpose of wireless communication of images in secure form. It considers two directions for image encryption: permutation-based encryption and diffusion-based encryption. Covering the range of image encryption principles and techniques, it presents hybrid encryption algorithms to enhance the characteristics of traditional algorithms. It explores number theory-based encryption algorithms, details the strength of different encryption algorithms, and describes their ability to work within the limitations of wireless communication systems.
Image Operators: Image Processing in Python
by Jason M. KinserFor decades, researchers have been developing algorithms to manipulate and analyze images. From this, a common set of image tools now appear in many high-level programming languages. Consequently, the amount of coding required by a user has significantly lessened over the years. While the libraries for image analysis are coalescing to a common toolkit, the language of image analysis has remained stagnant. Often, textual descriptions of an analytical protocol consume far more real estate than does the computer code required to execute the processes. Furthermore, the textual explanations are sometimes vague or incomplete. This book offers a precise mathematical language for the field of image processing. Defined operators correspond directly to standard library routines, greatly facilitating the translation between mathematical descriptions and computer script. This text is presented with Python 3 examples. This text will provide a unified language for image processing Provides the theoretical foundations with accompanied Python® scripts to precisely describe steps in image processing applications Linkage between scripts and theory through operators will be presented All chapters will contain theories, operator equivalents, examples, Python® codes, and exercises
Image Pattern Recognition: Fundamentals and Applications
by L Koteswara Rao Md. Zia Rahman P RohiniThis book describes various types of image patterns for image retrieval. All these patterns are texture dependent. Few image patterns such as Improved directional local extrema patterns, Local Quantized Extrema Patterns, Local Color Oppugnant Quantized Extrema Patterns and Local Mesh quantized extrema patterns are presented. Inter-relationships among the pixels of an image are used for feature extraction. In contrast to the existing patterns these patterns focus on local neighborhood of pixels to creates the feature vector. Evaluation metrics such as precision and recall are calculated after testing with standard databases i.e., Corel-1k, Corel-5k and MIT VisTex database. This book serves as a practical guide for students and researchers. -The text introduces two models of Directional local extrema patterns viz., Integration of color and directional local extrema patterns Integration of Gabor features and directional local extrema patterns. -Provides a framework to extract the features using quantization method -Discusses the local quantized extrema collected from two oppugnant color planes -Illustrates the mesh structure with the pixels at alternate positions.
Image Processing: Tensor Transform and Discrete Tomography with MATLAB ®
by Artyom M. Grigoryan Merughan M. GrigoryanFocusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB® introduces novel approaches to help in solving the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along parallel rays to more quickly and accurately reconstruct images from a finite number of projections, thereby avoiding overradiation of the body during a computed tomography (CT) scan. The book presents several new ideas, concepts, and methods, many of which have not been published elsewhere. New concepts include methods of transferring the geometry of rays from the plane to the Cartesian lattice, the point map of projections, the particle and its field function, and the statistical model of averaging. The authors supply numerous examples, MATLAB®-based programs, end-of-chapter problems, and experimental results of implementation. The main approach for image reconstruction proposed by the authors differs from existing methods of back-projection, iterative reconstruction, and Fourier and Radon filtering. In this book, the authors explain how to process each projection by a system of linear equations, or linear convolutions, to calculate the corresponding part of the 2-D tensor or paired transform of the discrete image. They then describe how to calculate the inverse transform to obtain the reconstruction. The proposed models for image reconstruction from projections are simple and result in more accurate reconstructions. Introducing a new theory and methods of image reconstruction, this book provides a solid grounding for those interested in further research and in obtaining new results. It encourages readers to develop effective applications of these methods in CT.
Image Processing: Dealing with Texture
by Maria M. Petrou Sei-ichiro KamataThe classic text that covers practical image processing methods and theory for image texture analysis, updated second edition The revised second edition of Image Processing: Dealing with Textures updates the classic work on texture analysis theory and methods without abandoning the foundational essentials of this landmark work. Like the first, the new edition offers an analysis of texture in digital images that are essential to a diverse range of applications such as: robotics, defense, medicine and the geo-sciences. Designed to easily locate information on specific problems, the text is structured around a series of helpful questions and answers. Updated to include the most recent developments in the field, many chapters have been completely revised including: Fractals and Multifractals, Image Statistics, Texture Repair, Local Phase Features, Dual Tree Complex Wavelet Transform, Ridgelets and Curvelets and Deep Texture Features. The book takes a two-level mathematical approach: light math is covered in the main level of the book, with harder math identified in separate boxes. This important text: Contains an update of the classic advanced text that reviews practical image processing methods and theory for image texture analysis Puts the focus exclusively on an in-depth exploration of texture Contains a companion website with exercises and algorithms Includes examples that are fully worked to enhance the learning experience Written for students and researchers of image processing, the second edition of Image Processing has been revised and updated to incorporate the foundational information on the topic and information on the latest advances.
Image Processing and Acquisition using Python (Chapman And Hall/crc Mathematical And Computational Imaging Sciences Ser.)
by Ravishankar Chityala Sridevi PudipeddiImage 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 effectiv
Image Processing and Acquisition using Python (Chapman & Hall/CRC The Python Series)
by Ravishankar Chityala Sridevi PudipeddiImage 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.