Since the digital image correlation (DIC) method based on the Newton-Raphson (N-R) method is sensitive to initial values, a reliable initial guess method which utilizes an image feature matching algorithm of speeded up robust features (SURF) is presented. The SURF algorithm can match the feature points of the images before and after deformation, and get the coordinate positions. The deformation parameter of a point of interest is initially estimated from the affine transformation which corresponds to the subset region of matched feature points. By iterating and optimizing the estimated values, the displacement which makes the zero-mean normalized sum of squared difference (ZNSSD) minimized is obtained. In the experiment, both the presented method and scale-invariant feature transform (SIFT) algorithm are used in the deformation measurement of carp scales stretching. It is shown that the proposed initialization method is more sufficiently accurate and can enable the subsequent N-R method to converge quickly.