Varved sediments are very useful for studies attempting to clarify the high-resolution record of paleoenvironments, because they are expected to contain annual or sub-annual records of depositional environments. In order to obtain annual records such as annual thicknesses, color tones, and chemical compositions, at the very least, it is necessary to detect the boundaries of annual bands. Additionally, such detection and thickness measurements should be reproducible. The detection of boundaries and the measurement of thicknesses in varved sediments are commonly carried out by megascopic or image analyses. However, human error and difficulties in assessment of reproducibility often accompany megascopic measurements. On the other hand, photographs, soft X-ray images (X-ray radiographs), and the results of XRF mapping can be used for image analysis. Image analysis methods such as the peak detection method and wavelet analysis attempt to detect varve boundaries and measure varve number and sedimentation rate; however, some difficulties remain in these analyses, especially for recognizing varve boundaries. In addition, wavelet analysis has low resolution for detecting individual lamina boundaries, and waveform analyses such as the peak detection method are not suited for data containing high-frequency physical noise.In this study, we applied a novel method for detecting lamina boundaries, especially in varved sediments, which is described by the following procedure: (1) smooth pixel values (gray value) of the lamina image, (2) map a maximum slope point of gray value in a square-shaped moving window (W1) on the image, (3) obtain a median gray value in a linear moving window (W2) along a stratigraphical section, and (4) detect lamina boundaries using a combination of the maximum slope point and the median value. An application of the lamina identification method of this study to a soft X-ray image of varved diatomite yielded a well-defined tricolored varve image and averaged transmittance value of soft X-rays in each lamina of the varve image. The thicknesses of varved sediments obtained using the tricolored image and the transmittance value of lamina can be easily converted into time series, and applied to spectral analyses.