Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move


Autoria(s): Nguyen Thanh, Kien; Fookes, Clinton B.; Sridharan, Sridha
Data(s)

01/08/2010

Resumo

Less cooperative iris identification systems at a distance and on the move often suffers from poor resolution. The lack of pixel resolution significantly degrades the iris recognition performance. Super-resolution has been considered to enhance resolution of iris images. This paper proposes a pixelwise super-resolution technique to reconstruct a high resolution iris image from a video sequence of an eye. A novel fusion approach is proposed to incorporate information details from multiple frames using robust mean. Experiments on the MBGC NIR portal database show the validity of the proposed approach in comparison with other resolution enhancement techniques.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/40916/

Publicador

ACM

Relação

http://eprints.qut.edu.au/40916/1/40916.pdf

http://soict.hut.vn/~soict2010/

Nguyen Thanh, Kien, Fookes, Clinton B., & Sridharan, Sridha (2010) Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move. In SoICT '10 Proceedings of the 2010 Symposium on Information and Communication Technology, ACM, Hanoi University of Technology, Hanoi, pp. 122-127.

Fonte

Faculty of Built Environment and Engineering

Palavras-Chave #080104 Computer Vision #090609 Signal Processing #iris recognition #super-resolution #robust mean #MBGC #iris at a distance and on the move
Tipo

Conference Paper