In this paper,a rapid nondestructive test method was established by computer vision and back propagation(BP) artificial neural network.It used in identifying dried meat floss and dried meat powder.The images of sixty dried meat floss and dried meat powder each were converted to gray and cut into 899×772 pixels.The gray mean,the total entropy,the standard deviation of gray scale matrix and contrast,correlation,energy and homogeneity based on gray level co-occurrence matrix were extracted from the cut gray images and the fractal dimension was extracted from the cut binary images.These eight texture indicators of forty-five dried meat floss and forty-four dried meat powder pre-processed images were used as the training set in training BP artificial neural network,and the rest samples were used as the test set.Results demonstrated that the total classification accuracy of the final BP artificial neural network was 80.65%.Two dried meat floss and four dried meat powder were miss classified.The study provided a rapid nondestructive analytical system for identifying dried meat floss and dried meat powder.