The feature matching step plays a critical role during the copy-move forgery detection procedure. However, when several highly similar features simultaneously exist in the feature space, current feature match- ing methods will miss a considerable number of genuine matching feature pairs. To this end, we propose a clustering-based method to collect qualified matching features for the feature point-based methods. The pro- posed method can collect far more genuine matching features than existing methods do, and thus significantly improve the detection performance, especially for multiple pasting cases. Experimental results confirm the effi- cacy of the proposed method. © 2015 SPIE and IS&T (DOI: 10.1117/1.JEI.24.2.023035)
['Liyang Yu', 'Qi Han', 'Xiamu Niu']
Qualified matching feature collection for feature point-based copy-move forgery detection