The rapid detection and identification of microorganisms is one of the most important factors in many cases of ill health. The purpose of this study was to determine the fluorescence characteristics of seven oral bacteria using emission spectra with the aim of distinguishing between the bacteria, and to compare fluorescence imaging methods for the direct assessment of oral bacteria. Fluorescence images of each bacterium were obtained under a 405‐nm light source using a two‐filter system. The emissions of all samples were measured with a fluorescence spectrometer. The complete fluorescence data set collected for each sample employed a three‐dimensional data cube. The differences in the autofluorescence characteristics of the seven oral bacteria were determined by principal components analysis (PCA). The fluorescence images of the oral bacteria varied with the genus and the filter system. The three‐dimensional excitation‐emission matrix fluorescence spectra exhibited distinctive fluorescence features associated with intracellular fluorophores. The seven bacteria could be clearly differentiated on the PCA score plot. The findings of this study indicate that oral bacteria can be identified based on their autofluorescence characteristics. Fluorescence spectroscopy coupled with PCA can be used to detect and classify oral bacteria. We visualized seven oral bacteria based on their auto‐fluorescence and distinguished by combining excitation emission matrix fluorescence spectroscopy data and PCA analysis. It offers a fundamental proof of reasoning to develop the auto‐fluorescence imaging for rapidly detection and identifying of bacteria. These methods can be expanded and implemented in clinical applications.