Earticle

초록

영어

Biometric has been implemented on numerous public facilities to enhance the security system. Fingerprint and face are the most popular biometric. Emerging technology has introduced potential biometric such as palm print, lips, teeth, vein and ear. However, most of this biometrics requires a special device to capture it. Thus, the implementation of such system will be costly. Iannarelli [1, 2] has proved that ear biometric is having a great potential for identifying a person. In this research work, an attempt is made to improve the detection and finally to segment the human ear from the whole image of human’s head. The success of this stage is very important for achieving the later goal, such as recognition and classification. This paper introduces a novel method for ear segmentation. Proposed method is based on morphological analysis fused with RBF neural network. Experiment shows that the proposed method has delivered a promising result.

목차

Abstract
 1. Introduction
 2. Proposed Hybrid Segmentation Method
 3. Development of a Pre-processing Method
 4. Development of a Classifier for Ear Edge Detection (s)
 5. Development of a Post-processing Method
 6. Experimental Results and Analysis
 7. Conclusions
 References

키워드

저자

• Mohammed J. Alhaddad [ King Abdul-Aziz University, Department of Information Technology Saudi Arabia, Jeddah ]
• Dzulkifli Mohamad [ King Abdul-Aziz University, Department of Information Technology Saudi Arabia, Jeddah ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605