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Recent research in texture-based ear recognition also indicates that ear detection and texture-based ear recognition are robust against signal degradation and encoding artefacts. Based on these findings, we further investigate and compare the performance of texture descriptors for ear recognition and seek to explore possibilities to complement texture descriptors with depth information. On the basis...
Ear classification refers to the process by which an input ear image is assigned to one of several pre-defined classes based on a set of features extracted from the image. In the context of large-scale ear identification, where the input probe image has to be compared against a large set of gallery images in order to locate a matching identity, classification can be used to restrict the matching process...
Due to the uniqueness and permanence properties of the biometric fingerprint characteristic, large scale in border control and governmental applications such as the Visa Information System (VIS) in Europe, US-VISIT / IDENT system in the USA and the Aadhaar project in India are based on fingerprint recognition. These systems generally contain millions of fingerprint samples. In order to improve the...
We present in this paper some lightweight metrics for quality assessment of fingerprint samples captured from a general-purposed optical camera using block-based autocorrelation and fast Walsh-Hadamard spectrum features. We generate a feature vector including 6 components in three categories to assess an image block's quality: (1) gray-scale values statistics, (2) autocorrelation based features, (3)...
It is becoming feasible and promising to use general purposed smartphone cameras as fingerprint scanners due to the rapidly improvement of smartphone hardware performance. We propose an approach to qualify the fingerprint samples generated by smartphones' cameras under real-life scenarios. Firstly, our approach extracts 6 quality features for each image block divided from a fingerprint sample using...
In identity retrieval from crime scene images, the outer ear (auricle) has ever since been regarded as a valuable characteristic. Because of its unique and permanent shape, the auricle also attracted the attention of researches in the field of biometrics over the last years. Since then, numerous pattern recognition techniques have been applied to ear images but similarly to face recognition, rotation...
Although a number of different ear recognition techniques have been proposed, not much work has been done in the field of ear detection. In this work we present a new ear detection approach for 3D profile images based on surface curvature and semantic analysis of edge-patterns. The algorithm applies edge-based detection techniques, which are known from 2D approaches, to a 3D data model. As an additional...
Accelerometer-based biometric gait recognition offers a convenient way to authenticate users on their mobile devices. Modern smartphones contain in-built accelerometers which can be used as sensors to acquire the necessary data while the subjects are walking. Hence, no additional costs for special sensors are imposed to the user. In this publication we extract several features from the gait data and...
Minutiae vicinity [1] captures a fingerprint's local topological information among neighboring minutiae for biometric template protection. We extend in this paper the definition of a minutia vicinity to a general one, which deems the conventional definition as a special case. Under this generalized definition, multiple vicinities can be obtained via defining different radial distances from one central...
This paper discusses the use of betti numbers to characterize fingerprint and iris images. The goal is to automatically separate fingerprint images from non-fingerprint images; where non-fingerprint images of special interest are biometric samples which are not fingerprints. In this regard, an image is viewed as a triangulated point cloud and the topology associated with this construct is summarized...
A local-area based fingerprint minutiae vicinity can be represented in a self-aligned way and achieves better robustness for recognition than a global minutiae template whose global geometric references (e.g., core or delta) are usually unstable to locate. However, local comparison based on vicinities ignores the global topology and thus still has potential to improve in performance if some stable...
We present an automatic 3D face recognition algorithm that is inspired by Alphonse Bertillon's anthropometry. Our recognition pipeline consists of several steps. First, the facial landmarks such as the tip of the nose or the inner eye corners are detected. Subsequently the head rotation is compensated during the orientation normalization process. The facial features are extracted by performing 61...
The goal of our research is to develop methods for accelerometer-based gait recognition, which are robust, stable and fast enough to be used for authentication on mobile devices. To show how far we are in reaching this goal we developed a new cycle extraction method, implemented an application for android phones and conducted a scenario test. We evaluated two different methods, which apply the same...
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