Department of Computer Science Dravidan University Kuppam – 517426 A.P INDIA
Abstract
We consider the problem of clustering a large set of images based on similarities of their noise patterns. Such clustering is necessary in forensic cases in which detection of common source of images is required, when the cameras are not physically available. We propose a novel method for clustering combining low dimensional embedding, visualization, and classical clustering of the dataset based on the similarity scores. We evaluate our method on the Dresden images database showing that the methodology is highly effective.
SARAVANA, S., & ANURADHA, P. T. (2021). Clustering Image Noise Patterns By Embedding And Visualization For Unknown Source Camera Detection. Int. J. of Aquatic Science, 12(3), 234-248.
MLA
S. SARAVANA; Prof T. ANURADHA. "Clustering Image Noise Patterns By Embedding And Visualization For Unknown Source Camera Detection". Int. J. of Aquatic Science, 12, 3, 2021, 234-248.
HARVARD
SARAVANA, S., ANURADHA, P. T. (2021). 'Clustering Image Noise Patterns By Embedding And Visualization For Unknown Source Camera Detection', Int. J. of Aquatic Science, 12(3), pp. 234-248.
VANCOUVER
SARAVANA, S., ANURADHA, P. T. Clustering Image Noise Patterns By Embedding And Visualization For Unknown Source Camera Detection. Int. J. of Aquatic Science, 2021; 12(3): 234-248.
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