Rapid recognition and detection of waterborne pathogens is of considerable significance for determining water quality and ensuring its safety. In this study, the multiwavelength transmission spectra of Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Salmonella typhimurium are measured. Further, a recognition method of bacterial species in water bodies is proposed based on the principle of similarity, cosine similarity, Pearson's correlation coefficient, and joint similarity algorithm. It is found that different similarity algorithms have different sensitivities to the spectral difference of different bacteria. The principle of similarity shows the highest recognition rate for Klebsiella pneumoniae, reaching 98.2%; remarkably, the recognition rate of cosine similarity and Pearson's correlation coefficient for Staphylococcus aureus are 100%. Joint similarity algorithm can realize the complementary advantages of different algorithms and effectively improve the reliability and stability of the recognition results. The recognition rates of joint similarity algorithm for low concentrations of Klebsiella pneumoniae, Staphylococcus aureus, Salmonella typhimurium, and Escherichia coli are 98.2%, 100%, 94.1%, and 91.4%, respectively, whereas the recognition rates for higher concentrations are 100%, 100%, 100%, and 96%, respectively.