ABSTRACT
This chapter presents an overview of the common processes, hardware and software technologies, and machine learning and image analysis techniques that are the foundation of machine vision systems. It provides a snapshot of the intelligent systems powered by machine vision technology that will help drive efficiency and productivity improvements in agriculture in the years to come. Machine vision systems are comprised of camera and computer hardware, software algorithms, and memory that interact in a conceptually similar manner to our human visual system to extract information from images and provide decision support or automation within a system. Machine vision systems are key components in phenotyping products and services. Learning methods are required in machine vision systems, since initially they have no knowledge of the target object. An agricultural production system can be generalized into seven top-level management themes are: preparation, protection, planting or rearing livestock, productivity, harvesting, processing and surveillance.
