Resonance based analysis of acoustic waves for 3D deep-layer fingerprint reconstruction

Traditional frequency based signal representation intends to decompose signals into superposition of sinusoids. Recently it has been shown that signals with oscillations can be well described via a new nonlinear signal decomposition method based on the concept of resonance. The objective of this paper is to introduce a resonance based analysis of A-scan signals in the prototyped multi-transducer acoustic imaging system for 3D fingerprint imaging. The proposed technology offers fingerprint pattern reconstruction from deeper layers of skin via sweat duct locations and epidermis structure. These additional characteristics, which are unique for any individual, provide information that can significantly facilitate fingerprint based identification. Since the reconstructed fingerprint is obtained from deeper layers, the method is robust against any manipulation, dirt or damage on surface of skin; the level of security and identification is more reliable. Experimental results are presented to illustrate the effectiveness of the approach.