Plaque is an unobservable biofilm on the tooth surface, which is a direct cause of a series of diseases such as dental caries and gingivitis. Early quantitative nondestructive detection of dental plaque is of great clinical importance. The bacteria of dental plaque and their metabolites can produce autofluorescence under short wavelength light excitation. The red fluorescence generated by a large amount of plaque under the excitation of 405nm blue light was collected based on the previous imaging system; the more mature the plaque, the higher the intensity of the red fluorescence; a modified U-net network was used to segment the red fluorescence, and the contour of the segmented plaque was extracted to obtain the core, and the teeth to which the plaque was attached were segmented using the area growth algorithm, and the plaque maturity and area were integrated to evaluate the plaque. The plaque maturity and area were combined to evaluate the plaque index. The results showed that the segmentation accuracy of the improved U-net network was better than that of the traditional method. The combination of plaque area and maturity degree to quantify dental plaque can eliminate the variability of human diagnosis to some extent.