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Abstract
This paper reviews developments since 2000 in the application of machine vision to food and agriculture. The subject involves applying radiation of various wavelengths to materials in order to find more about them: often this means looking not only at surfaces but also at internal structures. While visible light frequently provides enough useful information to make sound judgements, with the advent of dual energy X-ray (DEXA) detection, X-rays have been increasingly valuable. Perhaps the most exciting development is the 'spectral image cube' as an investigative tool. There have also been valuable developments in the use of three-dimensional methods, such as 'double Hough transforms' for the accurate delineation of crop rows, so that 'precision agriculture' can be realized, and the use of sets of visual calibration points so that robot vehicles can determine their exact locations and headings. Overall, the steady development of useful vision algorithms has been well matched by the capability of today's computers to implement them at sufficiently high speeds to make them viable.