• Aman
• Dr. Manoj Kumar Garg

“Nowadays in digital publishing, image forgery is the main issue and the system can be utilized for the purpose of forensic for the image authenticity validation. Image forgery authentication approach is presented in this paper. When any forgery or morphing is applied, homogeneity is lost from the image. In this paper, a proposed technique is presented utilizing the scale-invariant feature transform (SIFT) and support vector machine (SVM). Earlier, SVM failed in many cases for forged picture detection. Single extraction algorithm is not capable. So to overcome the drawbacks, image datasets are first fed to SIFT for feature extraction and the SVM is applied. The accuracy values are obtained by the proposed techniques for different images sets having different number of images. The obtained results by the proposed technique are also compared with the existing techniques. Accuracy obtained by the prosed technique is 91.46%.”

Image forgery; Scale-invariant Feature Transform; Support Vector Machine; Accuracy

"IMAGE FORGERY DETECTION AND CLASSIFICATION USING SUPPORT VECTOR MACHINE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 7, page no.f125-f135, July-2022, Available :http://www.jetir.org/papers/JETIR2207517.pdf

"IMAGE FORGERY DETECTION AND CLASSIFICATION USING SUPPORT VECTOR MACHINE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 7, page no. ppf125-f135, July-2022, Available at : http://www.jetir.org/papers/JETIR2207517.pdf