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Computer and Machine Vision: Theory, Algorithms, Practicalities [Anglais] [Relié]

E. R. Davies

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Description de l'ouvrage

18 avril 2012

Computer and Machine Vision: Theory, Algorithms, Practicalities (previously entitled Machine Vision) clearly and systematically presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fourth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date tutorial text suitable for graduate students, researchers and R&D engineers working in this vibrant subject.

Key features include:

  • Practical examples and case studies give the 'ins and outs' of developing real-world vision systems, giving engineers the realities of implementing the principles in practice.
  • New chapters containing case studies on surveillance and driver assistance systems give practical methods on these cutting-edge applications in computer vision.
  • Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples.
  • Updated content and new sections cover topics such as human iris location, image stitching, line detection using RANSAC, performance measures, and hyperspectral imaging.
  • The 'recent developments' section now included in each chapter will be useful in bringing students and practitioners up to date with the subject.

Roy Davies is Emeritus Professor of Machine Vision at Royal Holloway, University of London. He has worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests include automated visual inspection, surveillance, vehicle guidance and crime detection. He has published more than 200 papers, and three books - Machine Vision: Theory, Algorithms, Practicalities (1990), Electronics, Noise and Signal Recovery (1993), and Image Processing for the Food Industry (2000); the first of these has been widely used internationally for more than 20 years, and is now out in this much enhanced fourth edition. Roy holds a DSc at the University of London, and has been awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.




    • Mathematics and essential theory are made approachable by careful explanations and well-illustrated examples.
    • Updated content and new sections cover topics such as human iris location, image stitching, line detection using RANSAC, performance measures, and hyperspectral imaging.
    • The 'recent developments' section now included in each chapter will be useful in bringing students and practitioners up to date with the subject.

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    Biographie de l'auteur

    Roy Davies is a Professor of Machine Vision at Royal Holloway, University of London, and has extensive experience of machine vision, image analysis, automated visual inspection, and noise suppression techniques. His book Electronics, Noise, and Signal Recovery was published in 1993 by Academic Press, and is a useful companion to the present volume.

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    Couverture | Copyright | Table des matières | Extrait | Index
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    Commentaires en ligne 

    Il n'y a pas encore de commentaires clients sur Amazon.fr
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    Amazon.com: 5.0 étoiles sur 5  2 commentaires
    3 internautes sur 3 ont trouvé ce commentaire utile 
    5.0 étoiles sur 5 Great for DIA beginners. It just makes sense! 1 octobre 2012
    Par Amazon Customer - Publié sur Amazon.com
    Format:Format Kindle|Achat vérifié
    I am new to Digital Image Analysis, and am coming into this from a biology background. I've spent lots of money on DIA books, and this book is the first I've found that talks straight, and clear. It just makes sense. Although I am a newbie, I will venture to say the book is comprehensive in its coverage, so worth a look by anyone at any level. I can't say how much it would benefit an experienced person, but if you teach a course in this subject... TAKE NOTICE of this approach! The author is refreshingly concise and gets to the point and easily keeps my interest, which I really appreciate. It's actually a fun read! I am basically on a crash course in DIA. He follows with a commentary that really brings everything together, and into context, much like may occur in a lecture hall or discussion for a college course on the topic. He follows that with a thorough job of the most recent developments to date (as I write this, it is September 2012, and the book was published this year). He includes references to the most important papers historically in his comments, and the most important advances in the current literature in the final section on each topic. it's like having a complete, and very well organized literature review at your fingertips, as well as being a primer. I like that he keeps this lit review OUT of the straight forward explanations, so many books try to do it all in one place and it is just too much to cover and be clear. But it is extremely important, and by the time I get there, I know enough to appreciate it much, much more. There are also problem sets, and example photos in the book to illustrate the text. I am a person who discovered that I often benefit from going WAY back to old textbooks to get the basic information and understanding I need, because the newer authors can't fit that into their books anymore, and it's old hat to them anyway so they forget that not everyone knows it. Newbies really need the background! This is one science author who understands that, and the organization of the book is very effective. This book makes sense. THANK YOU DR. DAVIES!
    1 internautes sur 1 ont trouvé ce commentaire utile 
    5.0 étoiles sur 5 Important summary of the field, but not recommended as first reading 23 mars 2014
    Par Michael Stahl - Publié sur Amazon.com
    Format:Relié|Achat vérifié
    A very large book with a lot of information, starting from the very basics of computer vision, and up to very complicated challenges.

    The book's scope is huge, as it tried to summarize the whole field (the book is ~800 pages long). There are a lot of references to academic research for those interested in getting the whole details of math and research that this book is based on.

    The book goes from basic, low-level vision operations (filters; thresholding; edge, corner detection; morphology (erode and dilate)) to more complicated combinations:

    - Intermediate level vision: line, circle, ellipse detection, Hough transform, pattern matching)
    - 3D visions and motion (Invariants; perspective; camera calibration; motion; Kalman filter)
    - Real-time pattern recognition systems (reviewing a number of real-world applications)

    The book moves from readable to complicated, back and forth. There are a lot of mathematics (which I mostly skipped). The main problem with the math is that it is given in a very concise summary. More like a reminder for the already-initiated. So as an introductory book this math is lost on you as not all the pieces are there. It also makes for hard reading of these parts.

    I read this as my first book on Computer Vision. I learned a LOT from it, but I don't think it's a good recommendation as a first book. Too hard. Also, in most cases the math is not needed for what I do.

    Michael
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