Abstract
In an era characterized by digital interactions and security needs, biometric systems, especially hand geometry-based recognition, offer an advantageous solution. Biometric identification through hand geometry is ideal for low-security applications due to its non-invasive nature and user-friendly features. This research discusses personal identification leveraging hand geometry features, notably without the use of pegs. Such features encompass finger length and width, palm dimensions, deviations, and angles. Image capturing was conducted without pegs. The study contrasts the use of 12 versus 21 hand geometry features. Identification was achieved using the Euclidean distance measure. The outcomes were validated on both a local and a standard database.
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