An image Hashing algorithm based on structure features and gradient features was proposed to improve the classification performance and efficiency of Hashing algorithm. The input image is pre-processed to improve the robustness of the algorithm, and then the pre-processed image is transformed into YCbCr color space for extracting the brightness Y component. The external structure feature is obtained by using the peak and valley curves of Y component, and the internal structure feature is obtained by extracting the position information of the peak and valley. The external and internal structure features are combined to produce structure features of the image. The horizontal and vertical gradients of Y component are extracted to construct the gradient features. The final Hash is produced by combining and disturbing the structure features and gradient features. Experimental results show that the proposed algorithm is robust to some common content-preserving image processing such as brightness adjustment, contrast adjustment and Gaussian low-pass filtering. The proposed algorithm has better receiver operating characteristic（ROC） curve and better image classification performanc, compared with the existing Hashing algorithms. The tampering detection experiment shows that the algorithm can effectively detect tampered images.