Successful periodontal therapy requires sensitive techniques to discriminate dental calculus from healthy teeth. The aim of the present study was to develop a fluorescence-based procedure to enable real-time detection and quantification of dental calculus. Thirty human teeth--15 teeth with sub- and supragingival calculus and 15 healthy teeth--covered with a layer of physiological saline solution or blood were illuminated by a focused blue LED light source of 405 nm. Autofluorescence spectra recorded along a randomly selected line stretching over the crown-neck-root area of each tooth were utilized to evaluate a so called calculus parameter R, which was selected to define a relationship between the integrated intensities specific for healthy teeth and for calculus in the 477-497 nm (S(A)) and 628-685 nm (S(B)) wavelength regions, respectively. Statistical analysis was performed and a cut-off threshold of R=0.2 was found to distinguish dental calculus from healthy teeth with 100% sensitivity and specificity under various experimental conditions. The results of the spectral evaluation were confirmed by clinical and histological findings. Automated real-time detection and diagnostics for clinical use were implemented by a corresponding software program written in Visual Basic language. The method enables cost-effective and reliable calculus detection, and can be further developed for imaging applications.