Our previous paper [1] proposed to use Zernike moments magnitudes (ZMMs) of the image for authentication. We demonstrated the good robustness and discriminative capability of this feature vector and proposed a structure embedding method for the watermark generated from this feature vector to locate the tampered area. In this paper, we extend and improve the algorithm in [1] in the following ways: 1) embedding watermark in an image will affect its feature vector, we split the original image into several spaces randomly, one for generating feature vector, one for embedding ZMM based watermark. Thus, we can remove the effect of watermarking itself on the feature vector generating, 2) presenting a two-stage authentication method and improve the discriminating capability of the authentication. Compared with the existing approaches, the proposed scheme has better performance of discriminating high quality JPEG compression from malicious manipulations.