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An Improved Forgery Detection Method for Images
| Content Provider | Scilit |
|---|---|
| Author | Tom, Tiss Nandini, D. Usha Princemary, S. Ankayarkanni, B. |
| Copyright Year | 2019 |
| Description | Journal: Iop Conference Series: Materials Science and Engineering A forgery image detection system is introduced to detect the forgery in images using global, local and pixel based features. Global features will consider the whole images which include luminance and chrominance features. These global features can be extracted by using Zernike moments. The local feature consists of descriptors of multiple interest points. Image authentication is done by using hash method. The set of images will be trained in the database earlier itself. Then the test image and reference image will be compared based on pixels. By analyzing the hash distance the system can identify the test image is forged or not. As an improvement, pixel based feature extraction is used. Pixel based feature extraction is carried out by using supervised classification algorithm. |
| Related Links | https://iopscience.iop.org/article/10.1088/1757-899X/590/1/012032/pdf |
| ISSN | 17578981 |
| e-ISSN | 1757899X |
| DOI | 10.1088/1757-899x/590/1/012032 |
| Journal | Iop Conference Series: Materials Science and Engineering |
| Issue Number | 1 |
| Volume Number | 590 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2019-10-15 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Materials Science and Engineering Hardware and Architecture Characterization and Testing of Materials Forgery Image Pixel Based Feature Feature Extraction |
| Content Type | Text |
| Resource Type | Article |
