Ripe strawberry image segmentation is one of the primary problems of strawberry mechanization picking.Maximum entropy multiple threshold algorithm is one of the stability threshold methods in the image segmentationfield, but it has the shortcomings of high computational complexity and slow segmentation speed and so on. To re-duce its computational complexity and accelerate its search speed, an improved fast maximum entropy multiplethreshold strawberry image segmentation method（IFMEMT） was proposed in the paper. Firstly, the R componentgray images of RGB color images and their gray image information were extracted, and then applied IFMEMT algo-rithm, the maximum entropy and their corresponding thresholds were obtained; finally, the images were segmented.The experimental results showed that IFMEMT in a variety of complex environments could not only achieve thesame or even better segmentation effect than OTSU algorithm, but also had better segmentation efficiency, and itcould meet the real-time requirement of ripe strawberry mechanization picking.