Image Authentication Using Tensor Decomposition and Local Features with Geometric Correction

Abstract

In this paper, we proposed an image hashing using both global and local features. Global features are determined using tensor decomposition and local features are takeout from salient regions. SLIC algorithm are used to find out the salient area. The hash are constructed from global and local features. The test results on large dataset specify that the suggested method is vigorous to content-preserving operations (CPOs) and has good distinction. In addition, the method can also localize the tampering reigns. In this method, there are two phase. In the first phase,” the different image pairs” and “similar and tampered pairs” are segregated using threshold T1. In second phase, tampering localization and separation of. “the similar (authentic) image pairs” and “tampered image pairs” are carried out with another threshold T2. The receiver operating characteristics (ROC) indicate that this technique is superior than others.