The distribution of the three-dimensional footprint pressure surface reflects the behavioral and psychological characteristics of the human body. The segmentation and description of three-dimensional footprints are the basis of footprint biometric recognition. This paper proposes an interactive segmentation method of footprint depth images based on Gaussian curvature and mean curvature, which can intuitively and effectively segment the pressure surface area of interest. On this basis, a description method based on the global and regional features of the footprint is proposed. The features can reflect the inherent physiological characteristics of the human body and have strong robustness. Key words: heavy pressure surface, curvature, feature description Abstract: The distribution of footprint heavy pressure surface reflects the behavior feature and the physiological feature of human body. So, footprint heavy pressure surface pick-up and des cription is the foundation of footprint biological feature identification. We put forward a kind of footprint heavy pressure surfaces pick-up method based on Gauss curvature and average curvature. This method can pick-up effectively footprint heavy pressure surfacesthat we are interested. And on this foundation, we still put forward the des cription method based on footprint range image overall and regional features which can reflect the built-in biological feature of human body. The result of experiment shows that this des cription method is simple and practicality.Key words: heavy pressure surface, curvature, feature des cription
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