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    • 2. 发明专利
    • Design and Analysis of Image Forgery Detection Techniques for Innovative methodologies.
    • AU2021103274A4
    • 2022-03-24
    • AU2021103274
    • 2021-06-10
    • CHIKTE SHUBHANGI DIGAMBER DRPRATAPUR SATISH
    • CHIKTE SHUBHANGI DIGAMBERPRATAPUR SATISH
    • G06F21/10G06K9/00G06T1/00G06V10/46
    • [754] Our invention is a digital image forgery has turned out to be unsophisticated because of capable mobile, PCs, propelled image editing advanced defined software's and high resolution 128-bit, 255- bit or more capturing gadgets. Our Checking the quality of a respectability of color, non-color pictures and identifying hints of altering without requiring additional pre embedded data / information of the picture or installed unique watermarks are essential examine defined domain. [756] The Passive techniques do-not require pre-embedded data/ information in the image. The Several image forgery detection techniques are arranged first and after that their summed up local and global organization is produced. Our Invention increasingly dependent on the internet and so does it become more and more vulnerable to very harmful threats and also the threats are becoming vigorous. [758] These threats distort the valid authenticity of data transmitted through the internet and the as we all completely or partially rely upon this transmitted information data hence its authenticity needs to be develop. Our Images have the potential of conveying much more information as compared to the textual defined content and the I user ratty much believe everything that we see. The order to preserve/check the authenticity of images, image forgery detection techniques are expanding its domain. [760] The Detection of forgeries in digital images is in great need in order to recover the peoples trust in visual media and also our research is going to discuss all image forgery and defined blind methods for image forgery unique detection. TOTAL NO OF SHEET: 03 NO OF FIG: 03 blok-bFidmetod:oreyetoint-oresicmaeosflw Overlapping blocks Keyo4 t anftm Efficent Methodo agie [etr xr \110 11. r atcing114 1i8 Fig.1: Forgery Detection in Forensic Images flow.
    • 3. 发明专利
    • A Novel Watermarking Techniques for 3D Mesh Objects
    • AU2021102762A4
    • 2021-07-08
    • AU2021102762
    • 2021-05-22
    • CHIKTE SHUBHANGI DIGAMBER DRMALIPATIL MANIKAMMA
    • CHIKTE SHUBHANGI DIGAMBERMALIPATIL MANIKAMMA
    • G06T1/00G06T7/70G06T15/00G06T17/00G09C5/00H04N1/32
    • Title: A novel watermarking techniques for 3D mesh Objects Our invention A novel watermarking techniques for 3D mesh Objects is a context of 3D watermarking most of the state-of-the-art techniques analyze a 3D/3D clock wised approach where the insertion and the extraction of the mark take place over the object itself. The invention is also most common use of 3D-objects is done through its 2D -projections antilock wise and also a work in progress in the context of 3D-watermarking that introduces an asymmetrical approach 3D/2D which will allow the extraction of the mark without access to the 3D-object. The invention is a Building efficient data masking in encrypted images is an effective technique to mask data in the encrypted domain of 3D-mesh models and the original 3D-mesh models is encrypted Binary code (000111)) with a secret key and during or after its transmission it is possible to mask information in the encrypted-3D mesh models without knowing the original content of the 3D-mesh models. During the decoding process the secret message can be extracted and the original-3D mesh models can be reconstructed and also Data masking for 3D-mesh models has started to draw research interest and the development of cloud computing, data privacy has become a real-time face the problem. The invented methods allow us to hide a large amount of Data/ information in a reversible manner and the work we invented a new data masking method that is reversible in nature with a very high masking capacity. Experiment outcome shows the invented high-capacity data masking (HCDM) for 3D-mesh model attain better performance in terms of PSNR and RMSE over existing data masking methods. TOTAL NO OF SHEET: 04 NO OF FIG: 04 FIG.2: The Teapot model and a set of projections depending on the angle of visualization and also reconstructed from a certain number of its 2D representations.