Purpose To present a new automated image recognition software for the measurement of tear meniscus height (TMH) and investigate its correlation and efficacy compared with an open-source software (NIH ImageJ) and manual evaluation. Methods A total of 520 slit lamp photographs, among which 276 were in x16 magnification and 244 were x40 magnified, captured from 138 eyes of 69 healthy subjects were assessed for TMH by the new automated Tear Meniscus Identification Software (TMIS), ImageJ and human graders. Images processing of TMIS included filtration, recognition and measurement of slit lamp photographs under certain algorithm, which output two measurement patterns, TMISMax and TMISMean. TMH measured by ImageJ software, considered as the reference value, was conducted by a masked observer while four masked ophthalmologists performed the manual evaluation. Results In both magnifications, TMH measured by TMISMean showed similar values with ImageJ while manual evaluation demonstrated underestimated results, and a strong correlation was detected between TMIS and ImageJ. In x16 magnified photographs, manually obtained TMH revealed a higher correlation with ImageJ, whereas a notably stronger correlation of TMIS with ImageJ was observed in x40 photographs. Correspondingly, the accuracy for both TMISMax and TMISMean appeared to be lower than most doctors in x16 slit lamp images, in contrast to a better precision of TMISMean in x40 ones. Conclusion The new software displayed high accuracy and efficacy in x40 magnification and TMISMean pattern, suggesting the possibility of this automated TMH measurement platform to be a valid tool in dry eye screening and follow-up practice.