Splicing is a very common operation performed for image forgery. It involves merging of two or more different images to form a combined image that is significantly different from the original image. In this paper an image splicing detection method based on texture features of spliced image is proposed. The proposed approach calculates grey level run length matrix (GLRLM) texture features for the forged images and original images from CASIA database and DB2 database. The statistical features thus extracted from GLRLM are used for detection of tampering. Support vector machine is used for classification. The proposed algorithm is very effective in detection of splicing forgery as marked by the results.
No takes yet. Share an insight, caveat, or question.
Mushtaq et al. (2014) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: