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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(More)
This paper proposes an efficient indexing scheme that can be used for retrieval from a large iris database. For a given color iris query image, the proposed indexing scheme makes use of iris color to determine an index and uses this index to reduce the search space in the large iris database. Further, for query <i>q</i>, the retrieval technique uses iris(More)
This paper proposes an efficient indexing technique that can be used in an identification system with large multimodal biometric databases. The proposed technique is based on Kd-tree with feature level fusion which uses the multi-dimensional feature vector. A multi dimensional feature vector of each trait is first normalized and then, it is projected to a(More)
Face recognition is one of the most significant achievements in human vision. It has emerged that eigenface, neural network, graph matching, hidden markov model, geometrical feature matching ,template matching, 3D morphable model , line edge map (LEM) , support vector machine (SVM) ,multiple classifier systems (MCSs) are fashionable techniques of face(More)
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(More)
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(More)
Ear detection is a new class of relatively stable biometrics which is not affected by facial expressions, cosmetics, eye glasses and aging effects. Ear detection is the first step of an ear recognition system, to use ear biometrics for human identification. In this paper, we have presented two approaches to detect ear from 2D side face images. One is edge(More)