title: A biometric identification system based on eigenpalm and eigenfinger features.
abstract: This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).
authors.affiliation: Department of Electronics, Microelectronics, Computer, and Intelligent Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska, Croatia. slobodan.ribaric@fer.hr
authors.forename: Slobodan
authors.initials: S
authors.lastname: Ribaric
authors.forename: Ivan
authors.initials: I
authors.lastname: Fratric
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods*; D016494:Computer Security; D003878:Dermatoglyphics; D005385:Fingers / Q000033:anatomy & histology; D006225:Hand / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity