| An improved method for fast bacterial assessment with detailed information is a great challenge of microbial experiment revolution (MER). For example, the antibacterial activity of a composite is generally evaluated by its microbial test. The traditional method is the standard plate count method. It is an imprecise and time-consuming subjective process (1 day or more). When large numbers of bacteria are present, for example, using a concentration of 10 colony forming units (CFU) bacterial dilution, there are nearly thousand colonies on each plate. The reliability of the result is a major problem of this method. In addition; only several hundred cells are generally counted in one plate, which means statistical confidence is low. In principle, image-processing technique is capable of solving these problems. When appropriate image processing program is used, computer is able to perform image analysis faster than humans alone, with greater precision and more detailed information. Theoretically, with the aid of computer, automatic quantitative bacterial assessment should be feasible.High quality bacterial image is the foundation of accurate microbiological assessment. Confocal laser scanning microscopy (CLSM), a novel technique of optical sectioning microscopy, provides a powerful method to eliminate from images the background caused by out-of-focus light and scatter. CLSM can also improve the resolution of a light microscope image beyond what is achievable with normal fluorescence microscopy. In addition; digital acquisition of high-resolution images by CLSM enables rapid assessment of bacterial by image processing treatment.In this thesis, based on the high-resolution image from CLSM, a special image processing treatment was developed for the microbacterial assessment. We named this novel system as intelligent confocal laser scanning microscopy (ICLSM).The work is divided into six parts.
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