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Biometric systems can be attacked in several ways and the most common being spoofing the input sensor. Therefore, anti-spoofing is one of the most essential prerequisite against attacks on biometric systems. For face recognition it is even more vulnerable as the image capture is non-contact based. Several anti-spoofing methods have been proposed in the literature for both contact and non-contact based...
Face spoofing can be performed in a variety of ways such as replay attack, print attack, and mask attack to deceive an automated recognition algorithm. To mitigate the effect of spoofing attempts, face anti-spoofing approaches aim to distinguish between genuine samples and spoofed samples. The focus of this paper is to detect spoofing attempts via Haralick texture features. The proposed algorithm...
The performance of iris recognition reduces when the images are captured at a distance. However, such images generally contain periocular region which can be utilized for person recognition. In this research, we propose a novel context switching algorithm that dynamically selects the best descriptor for color iris and periocular regions. Using predefined protocols, the performance of the proposed...
The immune system in homo sapiens protects the body against diseases by identifying and attacking foreign pathogens. However, when the system misidentifies native cells as threats, it results in an auto-immune response. The auto-antibodies generated during this phenomenon may be identified through the indirect immunofluorescence test. An important constituent process of this test is the automated...
Collision-free navigation is an important problem in autonomous robots. In most of the applications, camera vision techniques using stereo-vision and laser scanners have been used. These techniques are not commercially viable for miniature robots due to size and computational limitations. Optical flow based models using monocular vision have shown promise in biomimetic systems to estimate depth information...
Over the years, iris recognition has gained importance in the biometrics applications and is being used in several large scale nationwide projects. Though iris patterns are unique, they may be affected by external factors such as illumination, camera-eye angle, and sensor interoperability. The presence of contact lens, particularly color cosmetic lens, may also pose a challenge to iris biometrics...
Face verification, though for humans seems to be an easy task, is a long-standing research area. With challenging covariates such as disguise or face obfuscation, automatically verifying the identity of a person is assumed to be very hard. This paper explores the feasibility of face verification under disguise variations using multi-spectrum (visible and thermal) face images. We propose a framework,...
Establishing kinship using images can be utilized as context information in different applications including face recognition. However, the process of automatically detecting kinship in facial images is a challenging and relatively less explored task. The reason for this includes limited availability of datasets as well as the inherent variations amongst kins. This paper presents a kinship classification...
This paper presents a novel fusion approach to combine scores from different biometric classifiers using Relevance Vector Machine. RVM uses a combination of kernel functions on training data for classification and compared to SVM, it requires significantly reduced number of relevance vectors. The proposed RVM based fusion algorithm is evaluated using a case study on multi-unit iris recognition. Experimental...
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