Abstract
The recapture detection based on high-quality LCD screen is really challenging as the recaptured image from LCD screen seems to be like the original and very difficult to distinguish by human eye. An image recapture detection algorithm is used to classify single captured and recaptured image. This paper proposes a novel approach for the reconstruction of recaptured images for improving quality using a dual dictionary of which, one is for single captured and the other for recaptured images. Here K-SVD algorithm is used to train both dictionaries in which the orthogonal matching pursuit algorithm has been used to generate sparse approximation from the dictionary of recaptured image and Line Spread Profile matrix. With the help of sparse approximation of recaptured set and dictionary of captured set, captured image can be reconstructed from recaptured image. The Experimental results indicate that the proposed algorithm results better quality of captured image from recaptured set in terms of PSNR.
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Hridhya, J., Shyna, A. (2018). Reconstruction of Recaptured Images Using Dual Dictionaries of Edge Profiles. In: Hemanth, D., Smys, S. (eds) Computational Vision and Bio Inspired Computing . Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71767-8_59
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DOI: https://doi.org/10.1007/978-3-319-71767-8_59
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