Modern Algorithms for Image Processing

Modern Algorithms for Image Processing

Vladimir Kovalevsky

49,60 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2019
ISBN:
9781484242384
49,60 €
IVA incluido
Disponible

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Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects in this book.Modern Algorithms for Image Processing approaches the topic of image processing through teaching by example. Throughout the book, you will create projects that resolve typical problems that you might encounter in the world of digital image processing. Some projects teach you methods for addressing the quality of images, such as reducing random errors or noise and suppressing pulse noise (salt and pepper), a method valuable for improving the quality of historical images. Other methods detail how to correct inhomogeneous illumination, not by means of subtracting the mean illumination, but through division, a far more efficient method. Additional projects cover contrasting, and a process for edge detection, more efficient than Canny’s, for detecting edges in color images directly, without converting them into black and white images.What You’ll LearnApply innovative methods for suppressing pulse noise, enhancing contrast, and edge detectionKnow the pros and cons of enlisting a particular methodUse new approaches for image compression and recognizing circles in photosUtilize a valuable method for straightening photos of paintings taken at an oblique angle, a critical concept to understand when using flash at a right angleUnderstand the problem statement of polygonal approximation of boundaries or edges and its solutionUse a new method for detecting bicycles in trafficAccess complete source code examples in C# for all of the projectsWho This Book Is ForC# developers who work with digital image processing or are interested in informatics. The reader should have programming experience and access to an integrated development environment (IDE), ideally .NET.This book does not prove or disprove theorems, but suggests methods for learning valuable concepts that will enable you to customize your own image processing projects.

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