Abstract: Objective: To establish a full digital automatic recognition system for palatal rugae and evaluate the results of forensic identification. Methods: Two-dimensional palatal rugae digital images were collected to establish a sample database, and then the palatal rugae samples were preprocessed. The palatal rugae image features were extracted by Gabor transform, and the extracted Gabor features were divided into blocks to avoid dimension disaster. The palatal rugae features after dividing were classified and recognized by the nearest neighbor classification algorithm. The forensic identification digital system based on palatine rugae image recognition was designed on the MATLAB software platform, and the two-dimensional palatal rugae images in the sample database were used as the experimental data for the experiment. The average correct matching rate and the average wrong matching rate were used to evaluate the forensic identification recognition performance. Results: By selecting different division scheme and reducing the dimensions of the extracted Gabor features, it could be found that the denser the blocks were, the better the recognition effect was, and the highest average correct matching rate could reach 97.8%. Conclusion: This new algorithm can achieve fast and accurate automatic recognition of palatal rugae image, and can be used as an alternative for identification in forensic science.

Key words: forensic stomatology, palatal rugae, forensic identification, feature extraction, feature dimension reduction