Online grading method for fresh-cut vegetables based on optimal invariant moment

In order to extract accurately fresh-cut vegetables from complex background of the image, an online classification method of fresh-cut vegetables was studied, which was based on the optimized moment invariant features model and integrates the two aspects of the moment invariant features?(translation and rotation) and the excellent scale expressing ability of the geometrical features. First, geometrical and moment invariant features of the standard fresh-cut vegetables was got, and a mathematical model was set up with statistics,; then two types features of fresh-cut vegetables to be graded was extracted; finally, similarity between the features of the sample and that of the standard fresh-cut vegetables so as to accomplish the online classification was made out. Take example of the fresh-cut pieces of potatoes, 11 images with 679 pieces of potatoes was disposed, and accuracy of the classification up to 99.40% , while it takes only 0.108 seconds to work on one image. The experiment shows that the method can classify exactly ,and have good real-time performance and robust result, and it can provide reference for the online classification of fresh-cut vegetables.