| Title |
Plagiarism Identification in Visual Communication Design: Construction of Similar Image Detection Model Based on Improved KAZE Algorithm |
| DOI |
https://doi.org/10.5573/IEIESPC.2025.14.5.569 |
| Keywords |
Visual communication design; Plagiarism identification; KAZE feature extraction; Feature; matching; Polar harmonic transform |
| Abstract |
In recent years, as the Internet technology develops, image processing software has gradually become popular, which provides convenience for plagiarism and tampering of images, and also brings difficulties to the protection of intellectual property rights. Therefore, how to quickly and accurately detect plagiarized and tampered images has become a top priority. In order to achieve accurate detection and location of plagiarized images, this paper puts forwards an image plagiarism detection model with KAZE and polar harmonic transform. Experimental results show that in the CoMoFoD database, the KAZE-polar harmonic transform algorithm can accurately identify images modified by copy-paste, brightness tampering, and blur processing. Compared with fuzzy C-means clusteringEmperor Penguin optimization-block feature matching algorithm and sparse recovery-key point matching algorithm, the average accuracy of KAZE-polar harmonic transform algorithm is 98.1%, which is higher than other algorithms, and each image The image recognition time only takes 10.86 s, which is faster than other algorithms. In the Coverage database, the KAZE-polar harmonic transformation algorithm can accurately identify and locate images with background tampering, and can effectively resist the interference of real similar objects; in addition, its average accuracy and image recognition speed are 90.3% and 11.5 s / Zhang, outperforms other algorithms. The above results show that the KAZE-polar harmonic transform algorithm proposed in the study can quickly and accurately identify and locate tampered pictures and tampered parts. |