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Titlebook: Digital Image Processing; An Algorithmic Intro Wilhelm Burger,Mark J. Burge Textbook 20223rd edition Springer Nature Switzerland AG 2022 Di

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書目名稱Digital Image Processing
副標(biāo)題An Algorithmic Intro
編輯Wilhelm Burger,Mark J. Burge
視頻videohttp://file.papertrans.cn/280/279437/279437.mp4
概述Presents an accessible introduction to the methods of digital image processing.Describes the most important procedures, with formal and mathematical aspects discussed at a fundamental level.Provides e
叢書名稱Texts in Computer Science
圖書封面Titlebook: Digital Image Processing; An Algorithmic Intro Wilhelm Burger,Mark J. Burge Textbook 20223rd edition Springer Nature Switzerland AG 2022 Di
描述This modern, self-contained textbook provides an accessible introduction to the field from?the perspective of a practicing programmer, supporting a detailed presentation of the?fundamental concepts and techniques with practical exercises and fully worked out?implementation examples. This much-anticipated 3rd edition of the definitive textbook on?Digital Image Processing has been completely revised and expanded with new content,?improved illustrations and teaching material..Topics and features:.Contains new chapters on fitting of geometric primitives, randomized feature?detection (RANSAC), and maximally stable extremal regions (MSER)..Includes exercises for most chapters and provides additional supplementary.materials and software implementations at an associated website..Uses ImageJ for all examples, a widely used open source imaging environment that.can run on allmajor platforms..Describes each solution in a stepwise manner in mathematical form, as abstract?pseudocode algorithms, and as complete Java programs that can be easily ported to?other programming languages..Presents suggested outlines for a one- or two-semester course in the preface..Advanced undergraduate and graduate st
出版日期Textbook 20223rd edition
關(guān)鍵詞Digital Image Processing; Discrete Fourier Transform; GSM - Postponed Project; Image Processing; Image P
版次3
doihttps://doi.org/10.1007/978-3-031-05744-1
isbn_softcover978-3-031-06343-5
isbn_ebook978-3-031-05744-1Series ISSN 1868-0941 Series E-ISSN 1868-095X
issn_series 1868-0941
copyrightSpringer Nature Switzerland AG 2022
The information of publication is updating

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Corner Detectionelated images (.), determining the correspondence between stereo images, serving as reference points for precise geometrical measurements, and calibrating camera systems for machine vision applications. Thus corner points are not only important in human vision but they are also “robust” in the sense
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Automatic Thresholding applications today because of their simplicity and efficiency. To obtain a binary image, the first and perhaps most critical step is to convert the initial grayscale (or color) image to a binary image, in most cases by performing some form of thresholding operation, as described in Sect. 3.1.4.
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Fitting Straight Lineses and, on the other hand, straight lines are quite rare in natural images. In this chapter we first look at how we can describe lines mathematically and which parameterizations are best suited for our purpose, which is how to fit a line to a given set of 2D data points under some optimality criteri
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Fitting Circles and Ellipsesine, physics, remote sensing, archeology, etc. Despite the classic nature of this problem, reliable and efficient algorithms have only been developed in the last few decades and are still a topic of active research. As with straight lines (see Ch. 10) the goal is to find an optimal orthogonal fit of
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Color Imagesprinting. Color perception is a fascinating and complicated phenomenon that has occupied the interests of scientists, psychologists, philosophers, and artists for hundreds of years [238, 246]. In this chapter, we focus on those technical aspects of color that are most important for working with digi
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