By their rapid and periodic actions, the cilia of the human respiratory tract play an important role in clearing inhaled noxious particles. Based on the automated image-processing technique, we studied the method analyzing ciliary beat frequency (CBF) objectively and quantitatively. Microscopic ciliary images were transformed into digitized gray ones through an image-grabber, and from these we extracted signals for CBF. By means of a FFT, maximum peak frequencies were detected as CBFs in each partitioned block for the entire digitized field. With these CBFs, we composed distribution maps visually showing the spatial distribution of CBFs. Through distribution maps of CBF, the whole aspects of CBF changes for cells and the difference of CBF of neighboring cells can be easily measured and detected. Histogram statistics calculated from the user-defined polygonal window can show the local dominant frequency presumed to be the CBF of a cell or a crust the region includes.