Ear Recognition Based on Centroid and Spindle
نویسندگان
چکیده
منابع مشابه
Human Identification based on Ear Recognition
Biometrics is the identification of humans based on their characteristics or traits. This paper presents the study of investigating the ear as an effective biometric trait in order to identify humans. The study involves using 2D images of ears and processing them to determine who the individual is. Various feature extraction techniques were explored. The study also presents many methods of clas...
متن کاملA Survey on Human Ear Recognition System Based on 2D and 3D Ear Images
Recognizing humans by their ear have recently received significant attention in the field of research. Ear is the rich in characteristics. The ear recognition does not suffer from some problems associated with other passive biometrics, such as face recognition and the ear shape very stable with respect to age. Further, the ear can be used for human recognition in surveillance videos where the f...
متن کامل3D Ear Normalization and Recognition Based on Local Surface Variation
Most existing ICP (Iterative Closet Point)-based 3D ear recognition approaches resort to the coarse-to-fine ICP algorithms to match 3D ear models. With such an approach, the gallery-probe pairs are coarsely aligned based on a few local feature points and then finely matched using the original ear point cloud. However, such an approach ignores the fact that not all the points in the coarsely seg...
متن کاملEar Recognition Based on Gabor Features and KFDA
We propose an ear recognition system based on 2D ear images which includes three stages: ear enrollment, feature extraction, and ear recognition. Ear enrollment includes ear detection and ear normalization. The ear detection approach based on improved Adaboost algorithm detects the ear part under complex background using two steps: offline cascaded classifier training and online ear detection. ...
متن کاملA 3D ear recognition method based on auricle structural feature
The performances of most existing 3D ear recognition methods are degraded sharply by pose variation. In this paper, a 3D ear representation called 3D auricle structural feature(3DASF) and the corresponding pose robust 3D ear recognition method is presented. By measuring the surface characteristics through Surface Variation, 3DASF that contains ear key physiological structure is extracted. Then ...
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ژورنال
عنوان ژورنال: Procedia Engineering
سال: 2012
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2012.01.280