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This paper models the messages embedded by spatial least significant bit (LSB) matching as independent noises to the cover image, and reveals that the histogram of the differences between pixel gray values is smoothed by the stego bits despite a large distance between the pixels. Using the characteristic function of difference histogram (DHCF), we prove that the center of mass of DHCF (DHCF COM) decreases after messages are embedded. Accordingly, the DHCF COMs are calculated as distinguishing features from the pixel pairs with different distances. The features are calibrated with an image generated by average operation, and then used to train a support vector machine (SVM) classifier. The experimental results prove that the features extracted from the differences between nonadjacent pixels can help to tackle LSB matching as well.