Every camera sensor leaves unique traces on the acquired images that can be thought of as a camera fingerprint. This work presents an efficient algorithm for clustering images based on their camera fingerprints. The algorithm performs a fast preliminary clustering based on a compressed representation of the camera fingerprints, then it refines the initial clusters using full-size fingerprints. The efficiency of the method is further improved by scanning the images according to a ranking index that depends on fingerprint estimation quality. The results confirm that the proposed method achieves a performance comparable to the state of the art approaches, with a significantly lower computational complexity, especially on large datasets. The method can also handle cases in which the number of clusters is much larger than the average size of the clusters.

每个摄像头传感器都会在获取的图像上留下独特的痕迹，这些痕迹可以被认为是摄像头指纹。这项工作提出了一种基于相机指纹对图像进行聚类的有效算法。该算法基于相机指纹的压缩表示执行快速的初步聚类，然后使用全尺寸指纹细化初始聚类。通过根据取决于指纹估计质量的等级索引扫描图像，进一步提高了该方法的效率。结果证实，所提出的方法以相当低的计算复杂度实现了与现有技术方法相当的性能，尤其是在大型数据集上。