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This paper proposes a multimodal biometric system through Gaussian mixture model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear...
This paper presents an efficient technique for automatic ear detection from side face images. The proposed technique detects ear by exploiting its inherent structural details and is rotation, scale and shape invariant. It can detect ear without any training or assuming prior knowledge of the input image. The technique is based on connected component analysis of a graph constructed using the edge map...
It is possible for vehicles moving on a highway to communicate with each other, if they are equipped with wireless interfaces. These vehicles, equipped with wireless connectivity, are referred to as nodes in a Vehicular Ad Hoc Network (VANET). The more the number of nodes involved in a network at a time, the more is the power consumed by them, thereby adding to the average power consumption of the...
Ear biometric is considered as one of the most reliable and invariant biometrics characteristics in line with iris and fingerprint characteristics. In many cases, ear biometrics can be compared with face biometrics regarding many physiological and texture characteristics. In this paper, a robust and efficient ear recognition system is presented, which uses Scale Invariant Feature Transform (SIFT)...
In this paper, a feature-level fusion approach for improving the efficiency of ear image verification is proposed. SIFT is used to extract the features on a ear images at different pose, which is then merged according to a fusion rule to produce a single feature called the fused template. The similarity of SIFT extracted features of the live image and the enrolled user template in the database is...
This paper proposes an efficient skin-color and template based technique for automatic ear detection in a side face image. The technique first separates skin regions from non skin regions and then searches for the ear within skin regions. Ear detection process involves three major steps. First, skin segmentation to eliminate all non-skin pixels from the image, second ear localization to perform ear...
The paper presents an efficient distance transform and template based technique for automatic ear localization from a side face image. The technique first segments skin and non-skin regions in the face and then uses template based approach to find the ear location within the skin regions. Ear detection proceeds as follows. First, edge map of the skin regions is computed and further processed to eliminate...
This paper presents an efficient approach for localization of ear from an arbitrary 2D side face image with varying background. Outer helix curves of ears moving parallel to each other are used as feature for localizing ear in an image. Using Canny edge detector, edges are extracted from the whole image. These edges are segmented in convex and concave edges. From these segmented edges expected outer...
With the increase in need for strong security systems, the biometric systems are becoming more and more popular. These systems are based on human traits which, unlike passwords or pins, cannot be lost, stolen or forgotten. One such trait is ear. With the initial doubts on uniqueness of ear, ear biometrics could not attract much attention. But after it has been said that it is almost impossible to...
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