Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.image.2020.116070 | SIGNAL PROCESSING-IMAGE COMMUNICATION |
Keywords | DocType | Volume |
Image clustering, Photo response non-uniformity, Computational complexity, Source camera identification | Journal | 91 |
ISSN | Citations | PageRank |
0923-5965 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sahib Khan | 1 | 0 | 2.03 |
| Tiziano Bianchi | 2 | 1003 | 62.55 |