Márcia V. P. do Nascimento
ABSTRACT
In the past years recognition by biometric information has been increasingly adopted. This paper presents a new approach to biometric recognition based on hand geometry. A database with 100 individuals and samples of both sides of the hands was used. The process prioritizes user comfort during capture and produces segmentation of hands and fingers with high precision. Altogether, 54 features have been extracted and different classification and training methods were evaluated. Tests using cross-validation and stratified random subsampling techniques were performed. The experiments demonstrated competitive results when compared to other state-of-the-art methods. The proposed approach obtained 100% accuracy using the Logist Boost together with Random Forest learning strategy and Bagging together with FLR combination.
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Index Terms
- A new approach to biometric recognition based on hand geometry
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