A multimodal biometric identification system using compressed finger images

作者：Khuwaja GA^*

来源：Cybernetics and Systems, 2006, 37(1): 23-46.

DOI：10.1080/01969720500320783

Finger image recognition remains one of the most prominent biometric identification methods. However, storage of finger databases needs allocation of huge secondary storage devices. In addition, there has been limited success in obtaining a satisfactory system due to the complexity of the problem. In this article, a low-cost, high-speed, multimodal biometric identification system trained with compressed finger images is presented with the objective to increase the overall matching confidence level. For this, three finger images of the left or right hand, or both, for one person are matched and the output decision is combined. A prototype optical-based finger-data acquisition system using the CCD (charge coupled device) digital still camera is adopted to capture a complete impression of finger area required for accurately identifying an individual. The acquired images then are compressed with a Coif5 wavelet packet-based scheme to increase the overall performance and eliminate bulk storage requirements. The finger image features are extracted with an adaptive neural network for the implementation of a three-finger multimodal system to achieve a peak identification rate of 100% (99.4% on average) in 0.15s for a database of 50 persons and 450 test images.

• 出版日期2006-2