Paper Info
Title
Fast Image Clustering Based on Camera Fingerprint Ordering
Abstract
This work presents a new camera fingerprint-based image clustering algorithm. The proposed algorithm is based on sorting the camera fingerprints according to information that is inherently present in images. A ranking index is constructed for each image, taking into account the combined effect of gray-level, saturation and texture on camera fingerprint estimation. Then, camera fingerprints are ordered according to this ranking index and clusters are iteratively constructed using as reference fingerprint the top-ranked fingerprint among the currently un-clustered fingerprints. The algorithm can be optionally implemented with an additional attraction stage to refine clustering. The results confirm that the proposed method achieves a performance comparable to state of the art approaches, with a significantly lower computational complexity. 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
2019
10.1109/ICME.2019.00137
2019 IEEE International Conference on Multimedia and Expo (ICME)
Keywords
Field
DocType
Image clustering,photo response non-uniformity,computational complexity
Cluster (physics),Computer vision,Pattern recognition,Ranking,Computer science,Sorting,Fingerprint,Artificial intelligence,Cluster analysis,Computational complexity theory
Conference
ISSN
ISBN
Citations 
1945-7871
978-1-5386-9553-1
0
PageRank 
References 
Authors
0.34
13
2
Name
Order
Citations
PageRank
Sahib Khan102.03
Tiziano Bianchi2100362.55