To Improve the Recognition Rate with High Security with Ear/Iris Biometric Recognition Technique with feature Extraction & Matching
Paridhi Agarwal · IOSR Journal of Computer Engineering · 2013
Ears are the new biometric with major advantage in that they appear to maintain their structure with increasing age.Contending that the ear is mainly a planar shape 2D images are used, which are consistent with deployment in surveillance and other planar-image scenarios.In this paper, a new model-based approach to ear biometrics is proposed.The model parts are derived by a stochastic clustering method on a set of scale invariant features on a training set.The model description is extended by proposing a new wavelet-based analysis with a specific aim of capturing information in the ear's outer structures.The performance is evaluated on test sets selected from the XM2VTS database.By results, both in modeling and recognition, the new modelbased approach does indeed appear to be a promising new approach to ear biometrics.The recognition performance has improved notably by the incorporation of the new wavelet-based analysis.A model-based approach has an advantage in handling noise and occlusion.A wavelet can offer performance advantages when handling occluded data by localization.A robust matching technique is also added to restrict the influence of corrupted wavelet projections.Furthermore, the automatic enrolment is tolerant of occlusion in ear samples.The hybrid method obtains promising results recognizing occluded ears.The results have confirmed the validity of this approach both in modeling and recognition.The new hybrid method does indeed appear to be a promising new approach to ear biometrics, by guiding a model-based analysis via anatomical knowledge.