• Title Computer Vision
• Author(s) Dana H. Ballard, Christopher M. Brown
• Publisher: Prentice Hall; First edition (May 1982)
• Hardcover 544 pages
• eBook PDF (539 pages, 140 MB)
• Language: English
• ISBN-10: 0131653164
• ISBN-13: 978-0131653160
• Share This:  

Book Description

This book is a hands-on introduction to computer vision using Python.

Computer vision is the construction of explicit, meaningful descriptions of physical objects from images. Image understanding is very different from image processing, which studies image-to-image transformations, not explicit description building.

Descriptions are a prerequisite for recognizing, manipulating, and thinking about objects. Parts of the book assume some mathematical and computing background (calculus, linear algebra, data structures, numerical methods).

However, throughout the book mathematical rigor takes a backseat to concepts. Our intent is to transmit a set of ideas about a new field to the widest possible audience.

• N/A

• Amazon

• Computer and Machine Vision
• Python Programming
• Data Structures and Algorithms
• Digital Signal Processing (DSP), Sound and Imaging Processing

• Computer Vision (Dana H. Ballard, et al)
• The Mirror Site (1) - PDF

• Distant Viewing: Computational Exploration of Digital Images

  This book presents a new theory and methodology for the application of computer vision methods to the computational analysis of collected, digitized visual materials, called “distant viewing”.

• Computer Vision: Algorithms and Applications, Second Edition

  This book explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications as well as for fun, consumer-level tasks.

• Computer Vision: Models, Learning, and Inference (Simon Prince)

  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. The detailed methodological presentation is useful for practitioners of computer vision.

• Programming Computer Vision with Python: Tools and Algorithms

  This book is a hands-on introduction to computer vision using Python. It gives an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers.

• Computer Vision Metrics: Survey, Taxonomy, and Analysis

  This book provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features.

• Mastering OpenCV 4: Computer Vision & Image Processing Apps

  This book targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, it delivers complete projects from ideation to running code, targeting current hot topics, etc.

• Computer Vision (Xiong Zhihui)

  This book presents computer vision on application of robotics, and on advanced approachs for computer vision (such as omnidirectional vision), research on RFID technology integrating stereo vision to localize an indoor mobile robot, etc.