Abstract
The use of millimetre wave images has been proposed recently in the biometric field to overcome certain limitations when using images acquired at visible frequencies. Furthermore, the security community has started using millimetre wave screening scanners in order to detect concealed objects. We believe we can exploit the use of these devices by incorporating biometric functionalities. This paper proposes a biometric recognition system based on the information of the silhouette of the human body, which may be seen as a type of soft biometric trait. To this aim, we report experimental results on the BIOGIGA database with four feature extraction approaches (contour coordinates, shape contexts, Fourier descriptors and landmarks) and three classification methods (Euclidean distance, dynamic time warping and support vector machines). The best configuration of 1.33 % EER is achieved when using contour coordinates with dynamic time warping.
Highlights
Many biometric characteristics are used to identify individuals: fingerprint, iris, voice, face, hand, signature etc
We observe that the equal error rate (EER) of the system decreases as the number of training images increases. It is worth noting the outstanding improvement of performance when applying dynamic time warping (DTW) algorithm to the contour coordinates and shape context approaches compared to the baseline Euclidean distance
Applying DTW to the Fourier descriptors does not result in better performance compared to Euclidean distance (ED) since these transformed features are already resampled to have the same dimension
Summary
Many biometric characteristics are used to identify individuals: fingerprint, iris, voice, face, hand, signature etc. The majority of these biometric traits are acquired with cameras working at visible frequencies of the electromagnetic spectrum. Such images are affected, among other factors, by lighting conditions and body occlusions (e.g. clothing, make up, hair etc.). Among other factors, by lighting conditions and body occlusions (e.g. clothing, make up, hair etc.) To overcome these limitations, researchers have proposed the use of images acquired at other spectral ranges: X-ray, infrared, millimetre (MMW) and submillimetre (SMW) waves [1]. Among the spectral bands out of the visible spectrum, the millimetre waves (with frequency in the band of 30–300 GHz) present interesting properties that can be exploited in biometrics: ability to pass through clothing and other occlusions, innocuous to health, low intrusiveness and the recent deployment and rapid progress of GHz-THz systems in screening applications
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