Imaging and machine vision book recommendations: 11/9

As part of our Solutions in Vision series, we want to provide our readers with as many resources on imaging and machine vision as possible. As part of this, Andy Wilson, Vision Systems Design Editor in Chief, has compiled a list of educational and informative books on various imaging topics that he personally recommends.

Content Dam Vsd En Articles 2015 11 Imaging And Machine Vision Book Recommendations 11 9 Leftcolumn Article Headerimage File

As part of ourSolutions in Vision series, we want to provide our readers with as many resources on imaging and machine vision as possible. As part of this, Andy Wilson, Vision Systems Design Editor in Chief, has compiled a list of educational and informative books on various imaging topics that he personally recommends. Check out this week’s recommendations here:

  • Template matching techniques in computer vision: theory and practice by Roberto Brunelli: The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications.
  • Handbook of Mathematical Models in Computer Vision by Nikos Paragios, Yunmei Chen, and Olivier D. Faugeras: This comprehensive volume is an essential reference tool for professional and academic researchers in the filed of computer vision, image processing, and applied mathematics. Continuing rapid advances in image processing have been enhanced by the theoretical efforts of mathematicians and engineers. This marriage of mathematics and computer vision - computational vision - has resulted in a discrete approach to image processing that is more reliable when leveraging in practical tasks.
  • An Introduction to 3D Computer Vision Techniques and Algorithmsby Boguslaw Cyganek and J. Paul Siebert: Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is possible to take a collection of stereo-pair images of a scene and then automatically produce a photo-realistic, geometrically accurate digital 3D model.
  • Computer Vision: A Modern Approachby David Forsyth and Jean Ponce: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies.
  • Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman: A basic problem in computer vision is to understand the structure of a real world scene. This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms.

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