Authors:
Milad Lankarany
and
Alireza Ahmadyfard
Affiliation:
Shahrood University of Technology, Iran, Islamic Republic of
Keyword(s):
Ear Biometrics, Ear Segmentation, Topographic Features.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
;
Surface Geometry and Shape
Abstract:
Ear segmentation is considered as the first step of all ear biometrics systems while the objective in separating the ear from its surrounding backgrounds is to improve the capability of automatic systems used for ear recognition. To meet this objective in the context of ear biometrics a new automatic algorithm based on topographic labels is presented here. The proposed algorithm contains four stages. First we extract topographic labels from the ear image. Then using the map of regions for three topographic labels namely, ridge, convex hill and convex saddle hill we build a composed set of labels. The thresholding on this labelled image provides a connected component with the maximum number of pixels which represents the outer boundary of the ear. As well as addressing faster implementation and brightness insensitivity, the technique is also validated by performing completely successful ear segmentation tested on “USTB” database which contains 308 profile view images of the ear and it
s surrounding backgrounds.
(More)