Plant disease detection and severity assessment are required for many purposes, including predicting yield loss, monitoring and forecasting epidemics, judging host resistance and for studying fundamental biological host–pathogen processes. If assessments of disease severity are inaccurate and/or imprecise, incorrect conclusions might be drawn and incorrect actions taken. Image analysis based on digital images made using visible wavelengths is one of the several methods used to detect and quantify disease; it offers advantages compared with visual assessment or other methods. Over the last 30 years, major advances have been made to improve reliability, precision and accuracy of image analysis for detecting and measuring plant disease. Although the equipment and software continue to become more sophisticated, these technologies are also becoming easier to use. As a result, image analysis to measure plant disease is becoming increasingly widely used, and has now been applied in the study of numerous plant diseases. This review describes the history, technology and application of visible-wavelength photography and image analysis, and progress towards realizing the full potential of these systems in plant disease detection and assessment