Copy-Move Geometric Tampering Estimation Through Enhanced SIFT Detector Method

Digital picture forgery detection has recently become a popular and significant topic in image processing. Due to advancements processing the availability of sophisticated software, fabrication may hide evidence hinder such criminal cases. The practice modifying original photographic images generate forged is known as digital forging. A section an copied pasted into another part same item or duplicate particular elements copy-move forgery. In order make forgeries real inconspicuous, geometric post-processing techniques are frequently performed on tampered regions during tampering process. Copy-Move detection, high similarity between source crucial evidence. most frequent way for detecting partition overlapping square blocks utilize Discrete cosine transform (DCT) components block representations. dimensionality feature space, Gaussian Radial basis function (RBF) kernel based Principal component analysis (PCA) used minimize vector representation, which improves matching efficiency. this paper, we propose use novel enhanced Scale-invariant (SIFT) detector method called RootSIFT, combined with measures mark areas image. proposed outperforms existing state-of-the-art methods terms time complexity, reliability, location accuracy, according experimental results. F1 score 92.3% while literature around 90% average.