An application of fractal image-set coding in facial recognition

Ebrahimpour Komleh, Hossein, Chandran, Vinod, & Sridharan, Subramanian (2004) An application of fractal image-set coding in facial recognition. In Zhang, D & Jain, A (Eds.) Biometric Authentication First International Conference (ICBA 2004) Proceedings, 15-17 July 2004, Hong Kong, China.

View at publisher


Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Impact and interest:

1 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 25066
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1007/978-3-540-25948-0_25
ISBN: 3-540-22146-8
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Deposited On: 17 Jun 2009 14:55
Last Modified: 25 Feb 2013 05:34

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page