The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
FIRE: fractal indexing with robust extensions for image databases
IEEE Transactions on Image Processing
A Self-tuning People Identification System from Split Face Components
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Normal maps vs. visible images: Comparing classifiers and combining modalities
Journal of Visual Languages and Computing
Face and ear: a bimodal identification system
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
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Due to growing demands in such application areas as law enforcement, video surveillance, banking, and security system access authentication, automatic face recognition has attracted great attention in recent years. The advantages of facial identification over alternative methods, such as fingerprint identification, are based primarily on the fact that face is fairly easy to use and well accepted by people. However it is not robust enough to be used in most practical security applications because too sensitive to variations in pose and illumination. During the last few years, many algorithms have been proposed to overcome these problems using 2-D images, but very few has been made in order to address the problem of partial occlusions. In this paper, a fractal based technique is presented; the face image is partitioned in different regions of interest, each one is indexed by means of an IFS system. A new distance function is then introduced, in order to discard unuseful information. The proposed method turns out to be faster and more robust than other approaches in the state of the art.