Umarani Jayaraman

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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 nonskin 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 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 multidimensional feature vector. A multi dimensional feature vector of each trait is first normalized and then, it is projected to a(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)
This paper proposes an efficient indexing technique for fingerprint database using minutiae based geometric hashing. A fixed length feature vector built from each minutia, known as Minutia Binary Pattern, has been suggested for the accurate match at the time of searching. Unlike existing geometric based indexing techniques, the proposed technique inserts(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)