Image analysis is driving a renaissance in growth measurement.

The domain of machine vision, in which digital images are acquired automatically in a highly structured environment for the purpose of computationally measuring features in the scene, is applicable to the measurement of plant growth. This article reviews the quickly growing collection of reports in which digital image-processing has been used to measure plant growth, with emphasis on the methodology and adaptations required for high-throughput studies of populations.