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Although biometrics technology has progressed substantially, its performance is still to be improved for real applications. This paper aims to improve the accuracy of personal identification, when only single sample is registered as template, by integrating multiple hand-based biometrics, i.e. palmprint and finger-knuckle-print. To make fusion much easier, the same feature, so called fusion code,...
In this paper, we propose a new theme-based CRF model and investigate its performance on class based pixel-wise segmentation of images. By including the theme of an image, we also propose a new texture-environment potential to represent texture environment of a pixel, which alone gives satisfactory recognition results. The pixel-wise segmentation accuracy is remarkably improved by introducing texture...
Given an image from a biometric sensor, it is important for the feature extraction module to extract an original set of features that can be used for identity recognition. This form of feature extraction has been referred to as Type I feature extraction. For some biometric systems, Type I feature extraction is used exclusively. However, a second form of feature extraction does exist and is concerned...
Because of its robustness, user friendliness, low cost and high accuracy, palmprint recognition has been widely studied in the past ten years. Various feature extraction and matching schemes have been proposed, among which the Gabor phase and orientation codes are very effective and efficient for palmprint representation and matching. Although these methods are adopted in the online palmprint recognition...
Palmprint images taken from a camera are distorted due to movement of a hand and fingers. To achieve reliable palmprint recognition, it is necessary to employ a recognition algorithm dealing with nonlinear distortion, while the conventional algorithms only consider the rigid body transformation between palmprint images. This paper proposes a palmprint recognition algorithm using phase-based correspondence...
Optic Disc (OD) localization is a fundamental step in developing computer-assisted diagnostics. In this work, an ultrafast method to locate the OD in retinal fundus images is presented. The proposed method is based on transforming the localization problem into two 1D problems by projecting the image features onto two perpendicular directions. Image features such as the directionality of the retinal...
Normalization is a particular important preprocessing operation, and has a large effect on the performance of character recognition. One of the purposes of normalization is to regulate the size, position, and shape of character images so as to reduce within-class shape variations. Among various methods of normalization, moment-based normalizations are known to greatly improve the performance of character...
Iris localization is the most important step in iris recognition systems, due to the fact that all the subsequent steps, iris normalization, feature extraction and matching, depends on its accuracy. Iris localization means segmentation of iris from the other parts of eye like pupil, sclera, eyelids and eyelashes in the image of an eye. A new method of exact pupil localization is proposed in this paper...
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