For the purpose of biometric applications, we explore in this paper a new approach to characterize palmprint features. In recent years, the contactless system emerges as a new viable option to address hygienic issues and improve the user acceptance. In this paper, we examine the issues related to the contactless imaging and we propose a new approach for palmprint recognition captured in contact...

In this paper, we propose an efficient palmprint recognition scheme which has two features: 1) representation of palm images by two dimensional (2-D) wavelet subband coefficients and 2) recognition by a modular, personalized classification method based on Kernel Principal Component Analysis (Kernel PCA). Wavelet subband coefficients can effectively capture substantial palm features while keepin...

The performance of two-dimension principal component analysis(2DPCA) is affected to some extent by illumination. In order to solve the problem, a new palmprint recognition algorithm based on entropy map(EM) and 2DPCA from a single image per person is developed. First, the EM of a single palmprint image is computed to eliminate the influence illumination on original grey image. Then the 2DPCA is...

Automatic palmprint identification has received much attention in security applications and law enforcement. The performance of a palmprint identification system is improved by means of feature extraction and classification. Feature extraction methods such as Subspace learning are highly sensitive to the rotation variances, translation and illumination in image identification. Thus, Histogram o...

Palm lines include principal lines and wrinkles, which can uniquely describe an individual palmprint. On motive of palmprint image enhancement is to highlight palm lines. In this paper, a steerable filters based fuzzy unsharp masking algorithm is presented to enhance the contrast of a palmprint image. This method introduces the fuzzy set theory into the unsharp masking scheme. Moreover, in the ...

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode ...

In the application of Biometric authentication, personal identification is regarded as an effective method for automatic recognition, with a high confidence, a person’s identity. Using multimodal biometric systems we typically get better performance compare to single biometric modality. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech...

Feature extraction is one of key technologies of the palmprint identification. In the light of the characteristics subspace palmprint identification technology, the two-dimensional principal component analysis, two-dimensional fisher linear discriminant and two-way two-dimensional principal component analysis algorithm is deeply analyzed. Based on two-dimensional subspace palmprint identificati...

This paper proposes two algorithms (k-mean clustering and back propagation) for palm recognition of an individual using geometrical and texture features. Palmprint recognition being one of the important aspects of biometric technology is one of the most reliable and successful identification methods. Thus palmprint recognition is a very interesting research area. In this study algorithm is prop...

Eigenpalms, a well-known approach, extracts features from palmprint images using conventional PCA technique. However eigenpalms does not exploit neighbourhood (local) information due to its vector representation of palmprint images. In our work here, we propose a feature-partitioning framework that uses a more efficient and appropriate matrix representation of images. Our novel feature partitio...