Since it has been reported that asbestos fibers cause serious health problems such as lung cancer, malignant mesothelioma and other related diseases, it turns into social issue leading to a number of studies for characterizing asbestos found in the indoor environment. Among the established methods for detecting asbestos fibers, phase contrast microscopy (PCM) method is widely used as it dose not require complicated process nor high-priced equipments. However, PCM method is hard to define a sort of asbestos and to detect tiny asbestos fibers. We developed an image-based high-throughput microscopy (HTM) for automated counting of asbestos fibers which were distinguishable from the spherical particles. HTM method enabled us to analyze asbestos fibers both automatically and quantitatively. Test samples of chrysotile, amosite and crocidolite, which are frequently detected in Korea, were used in this study and comparisons were made between concentrations of asbestos fibers measured by manual counting method and HTM method. Application of HTM system can be extended to various areas such as malaria diagnosis, rare cell detection and bacterial colony counting. Keywords：Asbestos, Phase contrast microscopy, High-throughput microscopy, Automated counting, Image processing