Recovery of 3D fingerprint data using photometric stereo generates 3D surface normal and albedo, which forms rich 3D fingerprint surface information. These surface normal's are further subjected to the reconstruction process, which integrates the surface normal to generate depth data. Since the source of depth information is essentially the surface normal, it is prudent to examine if this source information can itself be used for 3D fingerprint identification. In addition to avoiding the errors introduced by well-known integrability problem, such an approach can also enable significantly faster identification as the 3D reconstruction is the most computationally complex operation before the template matching. This paper investigates such an approach for 3D fingerprint identification using recovered surface normal and albedo information. We use publicly available 3D fingerprint database from 240 clients for the performance evaluation. The experimental results presented in this paper are highly promising, validates our approach, and indicate promises from matching contactless 3D fingerprints without the 3D surface reconstruction.