Image Fusion based Multi Resolution and Frequency Partition Discrete Cosine Transform for Palm Vein Recognition

Abstract

The rapid growth of technology has increased the demand for automated security systems. Due to the accessibility of the palm region and the unique characteristics of each individual's palm vein features, such biometrics have been receiving particular attention. In the published research relating to palm vein biometrics, usually only a single image is used to supply the data for recognition purposes. Previous experimental work has demonstrated that the fusion of multiple images is able to provide richer feature information resulting in an improved classification performance. However, although most of the image fusion techniques are able to preserve the vein pattern, the fused image is often blurred, the colors are distorted and the spatial resolution reduced. In this paper, the multiresolution discrete cosine transform (MRDCT) and frequency partition DCT (FPDCT) image fusion are applied and are able to extract the finer details of vein patterns while reducing the presence of noise in the image. The performance shows that the use of MRDCT and FPDCT was able to improve recognition rate compared to using a single image. The equal error rate improvement is also significant, falling to 9% in 700nm image, 7% in 850nm image and 6% in 940nm image.

Cost‐effective and accurate palm vein recognition system based on multiframe super‐resolution algorithms

“…Nevertheless, in view of the design principles and characteristics of the two PVR systems, we believe that the results may differ slightly even when the same dataset of palm images are used. Table 4 shows that our PVR system outperforms MRDCT, FPDCT, Wavelet, and EOL frameworks proposed by Soh et al [57], who used also the CASIA database of palm images. These results provide more insights into the role of MSR algorithms in the recognition of palm veins.…”

“…Table 4 shows that our PVR system outperforms MRDCT, FPDCT, Wavelet, and EOL frameworks proposed by Soh et al . [57], who used also the CASIA database of palm images. Although the results presented by Soh et al .…”

“…The MSR–PVR was compared with the classical PVR system proposed by Mirmohamadsadeghi and Drygajlo [51], which uses local binary patterns and local derivative patterns to facilitate the process of PVR. Additionally, our approach was compared with other state‐of‐the‐art methods that explore the capabilities of various image fusion techniques to improve the accuracy of the classical PVR system [57]. These techniques include multi‐resolution discrete cosine transform (MRDCT), frequency partition discrete cosine transform (FPDCT), wavelet, and energy of Laplacian (EOL).…”

Improving Palmprint based Biometric System Performance using Novel Multispectral Image Fusion Scheme

“…However, the image fusion techniques have shown good extraction of details of the vein patterns and excellent reduction of noise in the image. Also, the technique of FPDCT and MRDCT could enhance the recognition rate [30]. In the work done by J.-G. Wang et al, a novel method of fusion by locality preservation projections (LPP) was developed [31].…”