The invention discloses a two-dimensional Otsu image segmentation method in combination with a fruit fly optimization algorithm. The method adopts a two-dimensional histogram area divided by two straight lines passing through a threshold vector point and a gray-scale axis to form angles alpha and beta, and comprises the steps of calculating a joint probability density first, then calculating probabilities and mean vectors of a target area and a background area, calculating a between-class variance and a within-class variance of the target area and the background area, weighting the background area in a threshold solving formula according to the proportions of the target and the background in the image, and seeking an optimal two-dimensional threshold vector by adopting the fruit fly optimization algorithm. The method has the advantages of more accurate segmentation on pictures, better noise suppression and low running time consumption.