We present a set of texture parameters that correspond to perceptual properties of visual texture. For machine vision or a computer interface, it is important that the computational measurements of texture correspond well to the perceptual properties. To understand the mechanism of our visual system, it is important to know how we extract or characterize information for texture perception. In this study, we show that the autocorrelation function (ACF) analysis provides useful measures for representing three salient perceptual properties of texture: contrast, coarseness, and regularity. The validity of the ACF analysis was examined by comparing the calculated factors to the subjective scores collected for various kinds of natural textures. The effectiveness of the analysis depends on the structure of the estimated ACF. When a texture has a harmonic structure, the estimated ACF has periodical peaks corresponding to the periods of the texture. Both perceived coarseness and regularity are strongly related to these peaks in the ACF. However, the estimated ACF does not have a periodical structure when the texture is random. In this case, the texture coarseness and regularity are represented by the decay rate of the ACF.