Research Article Open Access

Multimodal Face and Ear Images

A.A. Darwish, R. Abd Elghafar and A. Fawzi Ali


Problem statement: The study presented in this study to combined face and ear algorithms as an application of human identification. Biometric system to the detection and identification of human faces and ears developed a multimodal biometric system using eigenfaces and eigenears. Approach: The proposed system used the extracted face and ear images to develop the respective feature spaces via the PCA algorithm called eigenfaces and eigenears, respectively. The proposed system showed promising results than individual face or ear biometrics investigated in the experiments. Results: The final achieve was then used to affirm the person as genuine or an impostor. System was tested on several databases and gave an overall accuracy of 92.24% with FAR of 10% and FRR of 6.1%. Conclusion: The results display if we combined face and ear is a good technique because it offered a high accuracy and security.

Journal of Computer Science
Volume 5 No. 5, 2009, 374-379


Submitted On: 8 May 2009 Published On: 30 May 2009

How to Cite: Darwish, A., Elghafar, R. A. & Ali, A. F. (2009). Multimodal Face and Ear Images. Journal of Computer Science, 5(5), 374-379.

  • 17 Citations



  • Face recognition
  • ear recognition
  • PCA
  • algorithms
  • eigenfaces
  • eigenears
  • pattern recognition