Yang, W; Ji, W; Xue, JH; Ren, Y; Liao, Q; (2019) A hybrid finger identification pattern using Polarized depth-Weighted Binary Direction Coding. Neurocomputing , 325 pp. 260-268. 10.1016/j.neucom.2018.10.042.

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Abstract

Finger identification is increasingly popular in recent years. In this paper, we propose a new finger identification system to acquire a hybrid pattern of dorsal finger vein and texture in a single image by using only one camera. It effectively reduces the cost and volume of the imaging device to acquire multi-modal patterns. The hybrid pattern of dorsal finger vein and texture is both storage-saving and calculation-saving. As there was no existing method specially developed for this kind of pattern, we propose a new feature extraction method called “Polarized depth-Weighted Binary Direction Coding” (PWBDC). We also establish a new database of such hybrid images of 210 finger samples. Experimental results demonstrate that the proposed system and feature are not only storage and calculation saving, but more importantly effective for identification. The proposed PWBDC method performs well on both the newly established database of hybrid images and a popular public database of traditional finger vein images, superior to many established and state-of-the-art methods.

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