Abstract

Background: With the development of three dimensional (3D) biometric recognition technologies, the 3D image recognition technology has encountered a great development space, and existed larger development bottleneck, also described in various patents. For example, in the process of imaging, there must be a lack of three-dimensional information of objects, resulting in low recognition rate.

Method: This paper analyzes the progress and technology development process of 3D biometric image recognition and discusses the main difficulties and future development direction. In these methods, the minimum distance method, correlation calculation method, nearest vector method, principal component analysis method, Markov model, support vector machine method and other various methods of 3D morphology are introduced in detail.

Result: The average recognition rate of the harmonic analysis algorithm is 98.5%, higher than the recognition rate of the ICP algorithm, which is 96.4%.

Conclusion: The experimental results verify the effect and the advantages and disadvantages of different methods, to provide the relevant content for studying on recognition of the 3D biometric features.

Keywords: Three dimensional (3D) biological features, Markov model, support vector, 3D morphology, harmonic analysis algorithm.