The salience of a contour depends upon several factors, including continuity, closure and curvature consistency. We analyze the statistics of curvature variation using a single image from Shimon Ullman’s [1] original work on contour salience. We develop a measure based on the arc length of a contour segment over which curvature variation remains within a constrained range. Locally, all contours in the image are similar with respect to curvature consistency. However, when the entire contour is considered, the most salient contours are found to have the most consistent curvatures. This finding reinforces Ullman’s point that salience is a global property of the object. We interpret these results in view of Rosenholtz’s [2] recent model of salience as a statistical measure of outliers from a population. In addition, we speculate on the visual cortical mechanisms in striate and extrastriate cortex required to carry out salience measurements on this class of images.