Three-dimensional palatal rugae recognition based on cyclic spectral analysis

Abstract

ObjectivePalatal rugae represent a new type of biometric characteristic that has a low cost and cannot be easily destroyed or forged. It can be used in forensic identification in special environments. However, prior research on palatal rugae recognition relied on the participation of forensic experts. In this study, a digital acquisition scheme of three-dimensional palatal rugae data is designed. MethodsAccording to the characteristics of palatal rugae, a cyclic spectrum is introduced as the recognition feature, and a k-nearest neighbor classifier is used to realize palatal rugae recognition. In addition, two strategies are utilized to reduce the computational complexity and information redundancy caused by the large dimension of three-dimensional data. Accordingly, isometric slicing is proposed to reduce the three-dimensional palatal rugae data dimension, and the cyclic spectral feature block partition scheme is then used to reduce the feature dimension. ResultsThe experimental results indicate that the accuracy of the proposed method is as high as 95 %. ConclusionThe proposed method uses pattern recognition technology to realize automatic palatal rugae recognition, which can reduce the dependence on forensic experts to achieve rapid forensic identification. SignificanceThis attempt is helpful in promoting the digitization of a forensic identification system based on palatal rugae.