Computer and Machine Vision

The application of intelligent imaging techniques to industrial vision problems is an evolving aspect of current machine vision research. Machine vision is a relatively new technology, more concerned with systems engineering than with computer science, and with much to offer the manufacturing industry in terms of improving efficiency, safety and product quality.

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

Vision plays a fundamental role for living beings by allowing them to interact with the environment in an effective and efficient way. The ultimate goal of Machine Vision is to endow artificial systems with adequate capabilities to cope with not a priori predetermined situations.

This book is a concise reference for professionals in a wide range of applications and vocations. It focuses on giving the reader mastery over the concepts, methods and metrics of digital video coding, so that readers have sufficient understanding to choose and tune coding parameters for optimum results that would suit their particular needs for quality, compression, speed and power.

How to use a Robot with Computer Vision in order to perform complex tasks, interacting with the surrounding environment, using a distributed system with several software communicating each others and exchanging data across the network.

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

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

Computer Vision Metrics 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. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications.

This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. First explain the foundations of system theory and image processing, before highlighting several modalities.

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

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.