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@article{179681,
        author = {Apeksha Ingle and Dr. C. N. Deshmukh and Dr. D. T. Ingole},
        title = {An Eficient Approach to Copy Move Forgery Detection using DWT and SIFT Features},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7877-7883},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179681},
        abstract = {The topic of copy move forgeries is becoming more and more popular among picture forensic experts. Essentially, copy move forgery involves replicating a single area in a picture by pasting a specific section of the same image onto it. Several methods have been employed to identify this kind of counterfeit. An improved method for identifying copy move forgeries is put forth in this research. To improve the robustness and accuracy of copy-move forgery detection, the suggested approach combines block-based techniques like Discrete Wavelet Transform (DWT) with feature-based techniques like Scale Invariant Feature Transform (SIFT). Initially, a picture is subjected to DWT in order to deconstruct it into four parts: LL, HL, HH, and LH. Since the majority of the information is contained in the LL component, SIFT is only applied to the LL part in order to further extract the image's essential features, match those features using interblock matching, identify the identical portion or portions between the images, and designate them as forged. This technique more precisely highlights the fraud and determines whether picture forgery has happened.},
        keywords = {},
        month = {May},
        }