Advanced method of face image processing and recognition based on Ssim technology

Author

Qian Chen

Author_Institution

Int. Sch., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2013

fDate

20-22 Dec. 2013

Firstpage

2500

Lastpage

2504

Abstract

Recent advances in information and network technologies make verifying the identity of the operator necessary. The most promising technological development in this sphere is face recognition technology. To elucidate the mechanism of face recognition, this paper reviews the relevant literature on face recognition technology. After a careful comparative analysis of the pros and cons of different technologies, an Advanced Multi-Reference Re-ranking (AMR) of face recognition technology was carried out. This method includes three main elements: Local Feature, Compressed Global Feature and Structural Similarity (SSIM). The results show that the use of Local Feature can improve the re-ranking speed and the Compressed Global Feature and SSIM enhance the accuracy of detection.

Keywords

face recognition; feature extraction; AMR; SSIM technology; advanced muitireference reranking; compressed global feature; face recognition technology; image processing; image recognition; information and network technologies; local feature; structural similarity; Artificial neural networks; Face; Face recognition; Image recognition; MATLAB; Principal component analysis; Robustness; Advanced Multi-Reference Reranking; Compressed Global Feature; Local Feature; Structural Similarity (SSIM); face recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on

Conference_Location

Shengyang

Print_ISBN

978-1-4799-2564-3

Type

conf

DOI

10.1109/MEC.2013.6885457

Filename

6885457