Multimodal biometric system based on palmprint using progressive image compression

In this paper, we propose a multimodal palmprint verification system based on two bands (gray scale and near infrared) using a progressive image compression through the famous Set Partitioning In Hierarchical Trees (SPIHT) coder. Each palmprint image is compressed an decompressed at 0.5 bit per pixel (bpp). By exploiting the progressiveness of the SPIHT algorithm, we decompressed the palmprint images in two bitrates. We obtained three images, an image at 0.25 bpp which represents the image approximation, the other at 0.25 bpp which represents the edges or details, and the third is the global of the both preceding. After analyzing the extracted features from different bands, we propose a score-level fusion scheme to integrate the multimodal information. The palmprint verification experiments demonstrated the superiority of multibands fusion to each single band, which results in higher verification accuracy.