Abstract
The technique of image processing is used to process information available in the pixels of an image. A forgery detection algorithm can detect any region of an image that has been copied earlier. This research work makes use of decision wavelet transform (DWT), and singular wavelet transform (SWT) approaches for copy-move forgery detection (CMFD). The presented SWT-DWT performs the detection tasks in different steps. These steps are known as preprocessing, feature extraction, feature matching, and forgery detection. The efficiency of the presented algorithm has been measured in terms of certain metrics.
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Sapra, P. (2022). Textural Feature Analysis Technique for Copy-Move Forgery Detection. In: Sanyal, G., Travieso-González, C.M., Awasthi, S., Pinto, C.M., Purushothama, B.R. (eds) International Conference on Artificial Intelligence and Sustainable Engineering. Lecture Notes in Electrical Engineering, vol 837. Springer, Singapore. https://doi.org/10.1007/978-981-16-8546-0_24
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