Aiming at the problems of selective harvesting-tomato for robot according to various purposes, feature extraction and analysis of tomato image from artificial selection were firstly performed. Proceeding from camera perspective geometry of tomato, difference value between rendering area ratio of red hue to whole tomato region and rendering area ratio of other hue to whole tomato region was presented by way of main grouping feature of judgment model to describe maturity of tomato. An automatic judgment model on maturity of tomato based on BP NN was built up by using above feature combined with hue mean and variance of whole rendering region of tomato. Validation test and noise level test of models show that the model can keep higher accuracy and nicer anti-interference when difference value of area ratio and hue mean are selected as two inputs of BP NN. The accuracy of validation test and noise level test is 97.5%. The accuracy can reach above 95.26% when noise level is under0.05. The model can provide theoretical reference of automatic harvesting-tomato for robot.