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006.6
Library items with class number 006.6



Computer vision / Simon J. D. Prince
Title : Computer vision : models, learning, and inference Material Type: printed text Authors: Simon J. D. Prince, Author Publisher: Cambridge : Cambridge University Press Publication Date: 2014 Pagination: xi, 580 p. Layout: ill. Size: 24 cm ISBN (or other code): 978-1-10-701179-3 General note: Includes bibliographical references (p. [533]-566)
Includes index (p. [567]-580)Languages : English (eng) Original Language : English (eng) Descriptors: Computer graphics
Computer visionClass number: 006.6 Abstract: This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision.
- Covers cutting-edge techniques, including graph cuts, machine learning, and multiple view geometry. - A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, face recognition, and object tracking.
- More than 70 algorithms are described in sufficient detail to implement.
- More than 350 full-color illustrations amplify the text.
- The treatment is self-contained, including all of the background mathematics.
- Additional resources at www.computervisionmodels.com.Contents note: Acknowledgments; Foreword by Andrew Fitzgibbon; Preface; Introduction; Probability; Introduction to probability; Common probability distributions; Fitting probability models; The normal distribution; Machine learning for machine vision; Learning and inference in vision; Modelling complex data densities; Regression models; Classification models; Connecting local models; Graphical models; Models for chains and trees; Models for grids; Pre-processing; Image pre-processing and feature extraction; Models for geometry; The pinhole camera; Models for transformations; Multiple cameras; Models for vision; Models for shape; Models for style and identity; Temporal models; Models for visual words; Appendices; Notation; Optimization; Linear algebra; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=16231 Hold
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Barcode Call number Media type Location Section Status 1702-001535 006.6 Pri-Com 2014 General Collection SEEU Library Skopje English Available Digital image processing / William K. Pratt
Title : Digital image processing : PIKS inside Material Type: printed text Authors: William K. Pratt, Author Edition statement: 3rd ed. Publisher: New York : J. Wiley & Sons Publication Date: 2001 Pagination: xix, 735 p. Layout: ill. (some col.) Size: 24 cm Accompanying material: CD ISBN (or other code): 978-0-471-37407-7 General note: Includes index Includes bibliographical references Languages : English (eng) Descriptors: Computer graphics
Image processing - Digital techniquesClass number: 006.6 Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=139 Hold
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Barcode Call number Media type Location Section Status 1702-000043 006.6 Pra-Dig 2001 General Collection SEEU Library Skopje English Available Feature extraction & image processing for computer vision / Mark S. Nixon
Title : Feature extraction & image processing for computer vision Material Type: printed text Authors: Mark S. Nixon, Author ; Alberto S. Aguado, Author Publisher: Elsevier/Academic Press, (Amsterdam -London) Publication Date: 2012 Pagination: xvii, 607 p. Layout: ill. Size: 24 cm ISBN (or other code): 978-0-12-396549-3 General note: Includes bibliographical references
Includes index (p. 601-607)Languages : English (eng) Original Language : English (eng) Descriptors: Computer graphics
Computer vision
Image processing - Digital techniques
Pattern recognition systems - Data processingClass number: 006.6 Abstract: This book is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Ada boost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. Contents note: Images, Sampling, and Frequency Domain Processing; Basic Image Processing Operations; Low-Level Feature Extraction (including edge detection); High-Level Feature Extraction: Fixed Shape Matching; High-Level Feature Extraction : Deform able Shape Analysis; Object Description; Introduction to Texture Description, Segmentation, and Classification; Moving Object Detection and and Description; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=16230 Hold
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Barcode Call number Media type Location Section Status 1702-001534 006.6 Nix-Fea 2012 General Collection SEEU Library Skopje English Available Fireworks MX fundamentals / Abigail Rudner
Title : Fireworks MX fundamentals Material Type: printed text Authors: Abigail Rudner, Author Publisher: Indianapolis, Ind. : New Riders Publication Date: 2003 Pagination: xxxiii, 539 p. Size: 24 cm Accompanying material: CD ISBN (or other code): 978-0-7357-1153-2 General note: Includes index (p. [513]-539) Languages : English (eng) Original Language : English (eng) Descriptors: Computer graphics
Fireworks (Computer file)Class number: 006.6 Abstract: Annotation An insiders look at the best practices for using and integrating Fireworks X effectively and efficiently. Expert advice from a 17-year graphics veteran who has used Fireworks since its inception. Focused pedagogy for intermediate users who want more than a button pushing guide. Real world context supplied by step-by-step tutorials to build useful sites. Fireworks is becoming much more important to web professionals because it is now being packaged along with Dreamweaver and Dreamweaver UltraDev. As more professionals note the easy interface between this graphics package and the web design software, more and more will begin to use Fireworks rather than put up with the hassles of integrating Photoshop with the Macromedia suite of web products. No one has yet prepared a book to address the needs of professional users who need more than the basics. Abigail Rudner is doing just that for New Riders, in the form of Inside Fireworks X. Abigail Rudner is a highly regarded member of the Fireworks Advisory Board and an author of Macromedia tutorials on Fireworks. Abigail is an experienced Designer working with such clients as Campbells, Tower Records, Apple Computers, Microsoft Corporation, Autodesk, BITSource, Kinetix, Absolut Vodka, Wall Street Journal, Wells Fargo, Levis, Bell Atlantic, Hewlett Packard, Lucent Technologies, and Deloitte Touche. Contents note: Getting up to speed; The meat of the matter; Making move and getting it out there; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=17487 Hold
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Barcode Call number Media type Location Section Status 1702-002033 006.6 Rud-Fir 2003 General Collection Library "Max van der Stoel" English Available Handbook of Computer Vision Algorithms in Image Algebra / Joseph N. Wilson
Title : Handbook of Computer Vision Algorithms in Image Algebra Material Type: printed text Authors: Joseph N. Wilson, Author ; Gerhard X. Ritter, Author Edition statement: 2nd edition Publisher: Boca Raton : CRC Publication Date: 2001 Pagination: 417 p. Layout: ill. Size: 24 cm ISBN (or other code): 978-0-84930-075-2 General note: Includes index (p. 413-417)
Includes bibliographical referencesLanguages : English (eng) Original Language : English (eng) Descriptors: Computer graphics
Computer vision
Image processing - Digital techniques
MathematicsClass number: 006.6 Abstract: Image algebra is a comprehensive, unifying theory of image transformations, image analysis, and image understanding. In 1996, the bestselling first edition of the Handbook of Computer Vision Algorithms in Image Algebra introduced engineers, scientists, and students to this powerful tool, its basic concepts, and its use in the concise representation of computer vision algorithms. Updated to reflect recent developments and advances, the second edition continues to provide an outstanding introduction to image algebra. It describes more than 80 fundamental computer vision techniques and introduces the portable C++ library, which supports image algebra programming in the C++ language. Revisions to the first edition include a new chapter on geometric manipulation and spatial transformation, several additional algorithms, and the addition of exercises to each chapter. Contents note: Image Algebra; Image Enhancement Techniques; Edge Detection and Boundary finding Techniques; Thresholding Techniques; Thinning and skeletonizing; Connected component Algorithms; Morphological transforms and Techniques; Linear Image Transforms; Pattern matching and Shape Detection; Image features and descriptors; Geometric image transformations; Neural Networks and cellular automat; Appendix. The Image Algebra C++ Library; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=16232 Hold
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Barcode Call number Media type Location Section Status 1702-001536 006.6 Wil-Han 2001 General Collection SEEU Library Skopje English Available Image Registration / Ardeshir Goshtasby
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