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Why do people attack monuments and other public objects charged with authority by the societies that produced them? What do open assaults on images and artworks mean? Iconoclasm, the principled destruction of images, has recurred throughout human history as theory and practice. This book contains seven historical studies of the changing causes and meanings of iconoclasm and the radical transformations in the function of images it has brought about in societies around the world, from Ancient Egypt to Islamic India and Revolutionary Mexico, as well as Medieval and Reformation Europe. Scholars of art history, history and archaeology explore shifting definitions of art and the forms of representation in delineating varied forms of 'iconoclasm'.
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.
According to the great mathematician Paul Erdös, God maintains perfect mathematical proofs in The Book. This book presents the authors candidates for such "perfect proofs," those which contain brilliant ideas, clever connections, and wonderful observations, bringing new insight and surprising perspectives to problems from number theory, geometry, analysis, combinatorics, and graph theory. As a result, this book will be fun reading for anyone with an interest in mathematics.
The use of computer-based image analysis systems for all kinds of images, but especially for microscope images, has become increasingly widespread in recent years, as computer power has increased and costs have dropped. Software to perform each of the various tasks described in this book exists now, and without doubt additional algorithms to accomplish these same things more efficiently, and to perform new kinds of image processing, feature discrimination and measurement, will continue to be developed. This is likely to be true particularly in the field of three-dimensional imaging, since new microscopy methods are beginning to be used which can produce such data. It is not the intent of this book to train programmers who will assemble their own computer systems and write their own programs. Most users require only the barest of knowledge about how to use the computer, but the greater their understanding of the various image analysis operations which are possible, their advantages and limitations, the greater the likelihood of success in their application. Likewise, the book assumes little in the way of a mathematical background, but the researcher with a secure knowledge of appropriate statistical tests will find it easier to put some of these methods into real use, and have confidence in the results, than one who has less background and experience. Supplementary texts and courses in statistics, microscopy, and specimen preparation are recommended as necessary.
Citizens of networked societies are almost incessantly accompanied by ecologies of images. These ecologies of still and moving images present a paradox of uncertainties emerging along with certainties. Images appear more certain as the technical capacities that render them visible increase. At the same time, images are touched by more uncertainty as their numbers, manipulabilities, and contingencies multiply. With the emergence of big data, the image is becoming a dominant vehicle for the construction and presentation of the truth of data. Images present themselves as so many promises of the certainty, predictability, and intelligibility offered by data. The focus of this book is twofold. It analyses the kinds of images appearing today, showing how they are marked by a return to modern photographic emphases on high resolution, clarity, and realistic representation. Secondly, it discusses the ways in which the uncertainty of images is increasingly underscored within such reiterated emphases on allegedly certain visual truths. This often involves renewed encounters with noise, grain, glitch, blur, vagueness, and indistinctness. This book provides the reader with an intriguing transdisciplinary investigation of the uncertainly certain relation between the cultural imagination and the techno-aesthetic regime of big data and ubiquitous computing. This book was originally published as a special issue of Digital Creativity.
Images increasingly saturate our world, making present to us what is distant or obscure. Yet the power of images also arises from what they do not make present—from a type of absence they do not dispel. Joining a growing multidisciplinary conversation that rejects an understanding of images as lifeless objects, this book offers a theological meditation on the ways images convey presence into our world. Just as Christ negates himself in order to manifest the invisible God, images, Natalie Carnes contends, negate themselves to give more than they literally or materially are. Her Christological reflections bring iconoclasm and iconophilia into productive relation, suggesting that they need not oppose one another. Investigating such images as the biblical golden calf and paintings of the Virgin Mary, Carnes explores how to distinguish between iconoclasms that maintain fidelity to their theological intentions and those that lead to visual temptation. Offering ecumenical reflections on issues that have long divided Protestant, Catholic, and Orthodox traditions, Image and Presence provokes a fundamental reconsideration of images and of the global image crises of our time.
The book examines how well we remember what we see. It pulls together the field with a series of chapters that concisely present the state-of-the-science in all the areas of research.
As speaking animals, we continuously make use of an unassuming grammatical particle, without suspecting that what is at work in its inconspicuousness is a powerful apparatus, which orchestrates language, signification, and the world at large. What particle might this be? The word not. In Essay on Negation, Paolo Virno argues that the importance of the not is perhaps comparable only to that of money--that is, the universality of exchange. Negation is what separates verbal thought from silent cognitive operations, such as feelings and mental images. Speaking about what is not happening here and now, or about properties that are not referable to a given object, the human animal deactivates its original neuronal empathy, which is prelinguistic; it distances itself from the prescriptions of its own instinctual endowment and accesses a higher sociality, negotiated and unstable, which establishes the public sphere. In fact, the speaking animal soon learns that the negative statement does not amount to the linguistic double of unpleasant realities or destructive emotions: while it rejects them, negation also names them and thus includes them in social life. Virno sees negation as a crucial effect of civilization, one that is, however, also always exposed to further regressions. Taking his cue from a humble word, the author is capable of unfolding the unexpected phenomenology of the negating consciousness.
Methods, Measures, and Theories in Eyewitness Recognition Tasks provides a comprehensive review of the fundamental issues surrounding eyewitness recognition phenomena alongside suggestions for developing a more methodologically rigorous eyewitness science. Over the past 40 years, the field of eyewitness science has seen substantial advancement in eyewitness identification procedures, yet theoretical and methodological developments have fallen behind. Featuring contributions from prominent international scholars, this book examines methodological and theoretical limitations and explores important topics, including how to increase the accuracy of identifying perpetrators when using CCTV images, how to create more identifiable facial composites, and the differences in accuracy between younger and older eyewitnesses. Providing in-depth discussion on the limitations of traditional lineups, eyewitness memory fallibility, and the complications that arise when using laboratory simulations, along with suggestions for new methods, this book will be an invaluable resource for researchers in eyewitness recognition, lawyers, players in the criminal justice system, members of innocence commissions, and researchers with interests in cognitive psychology.