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:
- Computer Vision and Applications: A Guide for Students and Practitioners byBernd Jahne: Based on the highly successful 3-volume reference Handbook of Computer Vision and Applications, this concise edition covers in a single volume the entire spectrum of computer vision ranging form the imaging process to high-end algorithms and applications. This book consists of three parts, including an application gallery, and is accompanied by an interactive CD-ROM.
- Emerging Topics in Computer Vision by Gerard Medioni and Sing Bing Kang: The popularity of topics in computer vision shifts periodically, precipitated by what actually works or shows great promise, changing interests in applications, and on occasion, fortuitous advancements in hardware technology. Some of these topics remain popular over the years, such as facial recognition and modeling from images, while others are relatively new, such as computer vision techniques for graphics and the application of level-set theory in computer vision.
- 2D Object Detection and Recognition: Models, Algorithms, and Networksby Yali Amit: Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approaches to efficient implementation, and parallel implementations in biologically plausible neural network architectures.
- Handbook of Computer Vision Algorithms in Image Algebraby Joseph N. Wilson and Gerhard X. Ritter: 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.
- Introduction to Machine Visionby Ramesh C. Jain and Rangacher Kasturi: Focuses on basic concepts and techniques in the field of computer vision. Covering binary vision, segmentation, constraint propagation techniques, camera calibration, and detection of motion, this text provides instruction and theory for developing a functioning machine vision system.
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