We propose a novel cryptographic construct incorporating biometrics which insures a secure
communication between two channels just by using Palmprint. The cryptosystem utilizes the
advantages of both symmetric and asymmetric cryptographic approaches simultaneously; we denote
it as double encryption. Any document in communication is first encrypted using symmetric
cryptographic approach; the symmetric key involved is then encrypted using Asymmetric approach.
Finally, the concept of fuzzy vault is explored to create a secure vault around the asymmetric key. We
investigate the possible usage of palmprints in fuzzy vault to develop a user friendly and reliable
crypto system. The experimental results from the proposed approach on the real palmprint images
suggest its possible usage in an automated palmprint based key generation system.
This paper presents a new approach to authenticate individuals using triangulation of hand vein images. The proposed method is fully automated and employs palm dorsal hand vein images acquired from the low-cost, near infrared, contactless imaging. The knuckle tips are used as key points for image normalization and the extraction of region of interest. The matching scores are generated in two parallel stages; (i) hierarchical matching score from the four topologies of triangulation in binarized vein structures and (ii) from the geometrical features consisting of knuckle point perimeter distances in the acquired images. The weighted score level combination from these two matching scores are used to authenticate the individuals. The achieved experimental results from the proposed system using contactless, palm dorsal hand vein images are promising and suggest more user friendly alternative for user identification.
This paper investigates a new approach for human ear identification using holistic
grey-level information. We employ Log-Gabor wavelets to extract the phase
information, i.e. ear-codes, from the 1D gray-level signals. Thus each ear is
represented by a unique ear code or (phase template). The query ear images are
compared with those in the database using Hamming distance. The minimum
Hamming distance obtained from the rotation of ear template is used to authenticate
the user. Our experiments on two different public ear databases achieve promising
results and suggest its utility in ear-based authentication. This paper also illustrates
that the phase information extracted from ear images can achieve significant
performance improvement as compared to appearance-based approach employed in
Modern infrared imaging systems are designed based on highly sensitive infrared focal plane arrays (IRFPA), in which most of the preprocessing is done on the focal plane itself. In spite of many advances in the design of IRFPAs, it has inherent non-uniformities and instabilities, which limits its sensitivity, dynamic range and other advantages. Whenever there is little or no thermal variation in the scene, the thermal imager suffers from its inability to separate out the target of interest from its background. Thus, most of the infrared imagery suffers from poor contrast and high noise. A methodology for contrast enhancement that combines the fuzzy based processing and spatial processing is proposed. Fuzzy based processing improves the image where there are inaccuracies and uncertainties in the image, where as spatial processing is used for improving the contrast and enhancing the details. This results the overall improvement in the image quality under all conditions. This algorithm has been tested on the field-recorded data and is observed that this technique offers excellent results for thermal imager operating in both 3-5 μm and 8-12 μm wavelength regions.
This paper investigates the performance improvement for palmprint authentication using multiple classifiers. The proposed methods on personal authentication using palmprints can be divided into three categories; appearance- , line -, and texture-based. A combination of these approaches can be used to achieve higher performance. We propose to simultaneously extract palmprint features from PCA, Line detectors and Gabor-filters and combine their corresponding matching scores. This paper also investigates the comparative performance of simple combination rules and the hybrid fusion strategy to achieve performance improvement. Our experimental results on the database of 100 users demonstrate the usefulness of such approach over those based on individual classifiers.
Quality assurance is the key for increasing competition in the market place. This paper presents a new machine vision based approach for the detection of defects using real Gabor functions. A bank of real Gabor functions, followed by a nonlinear function, is used to sample texture features at different scales. These texture features are compared with those from defect-free (reference) image, and a set of feature difference arrays are created. These are used to generate a combined image output using image fusion. This combined image output is used to obtain a binary image of defects using calibration. This paper also details a new method for automated selection of the center frequency of Gabor function using spectral analysis. Experimental results have confirmed the usefulness of the proposed approach for the automated inspection of textile webs.