图像摘要（Hash）是将数字图像映射为一串短的数，在图像认证、图像内容检索、数字水印等方面有广泛应用。提出了应用Harris角点检测和奇异值分解的图像Hash算法，首先在图像中选取对灰度变化和旋转稳健的Harris角点，对这些稳健特征点周围图像块的奇异值进行量化以实现数据压缩，经编码产生图像Hash。该算法建立在稳健特征点检测基础上，结合了特征点的位置和周围图像信息，得到的Hash对视觉可接受的几何变换、亮度和对比度变化、JPEG压缩具有良好的稳健性，而大幅度扰动或篡改则会改变Hash值。密钥的使用保证了Hash的安全性。

Perceptual image hashing maps an image to a short data string, applicable to image authentication, content based image retrieval, digital watermarking, etc. We propose a new image hashing algorithm using Harris corners and singular value decomposition. Critical feature points robust against gray level modification and image rotation are identified. A prescribed number of large singular values of the image blocks centered at the robust feature points are quantized to compress the data, which represent positions of the points and information of their neighborhood. The compressed data are then coded to generate the hash. The obtained hash is stable to visually insignificant changes due to normal image processing and JPEG coding, while sensitive to excessive changes and malicious tampering. Security of the hash is guaranteed by using secret keys.