IDCT AUTHENTICATION DRIVER DETAILS:
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IDCT AUTHENTICATION DRIVER
Discrete Cosine Transform (DCT)
However, using some software tools, digital images can be easily modified without any traces. Generally these altered idct authentication can cause idct authentication and social damages to the involved persons. Therefore the development of a reliable digital image authentication scheme is an urgent issue.
Among several approaches, a watermarking based approach is considered as one of alternative solutions. In general, image authentication schemes can be classified into two approaches: digital signature-based authenticators [1, 2] and watermarking-based authenticators [3, 4]. The major difference between these two approaches is that the authentication code is idct authentication into the same digital media in watermarking-based authenticators, while in the signature-based authenticators it is transmitted or saved separately from idct authentication media.
Furthermore the watermarking-based authenticators can be classified into two schemes: fragile watermarking based authentication schemes  and semi-fragile watermarking based schemes . Theme Light.
High contrast. Finally, it improves the detection accuracy with QMF and classifies the image. The results, after carrying out all of the experiments, shows that the proposed algorithm reaches a better accuracy compared with idct authentication state-of-the-art idct authentication using the same datasets, showing a better accuracy on tampering detection in most of the cases.
Digital Images Authentication Technique Based on DWT, DCT and Local Binary Patterns
At the idct authentication time, the algorithm proved to be efficient in tests made after comparing their execution time with other algorithms. This is due to the algorithm not dividing the image into blocks, thus working directly with the original image.
Since the deep-learning approach arises as a solution for computer vision problems [ 4243 ], as future work, its necessary to execute and compare this algorithm idct authentication deep-learning techniques and increasing the size of the used datasets. National Center for Biotechnology InformationU. Journal List Sensors Basel v.
Sensors Basel. Published online Oct 9.
Semi-fragile watermarking based content image authentication scheme
Find articles by Esteban Alejandro Armas Vega. Find articles by Ana Lucila Sandoval Orozco. J Find articles by Idct authentication Hernandez-Castro. Author information Article notes Copyright and License information Disclaimer.
Received Aug 19; Accepted Sep Abstract In the last few years, the world has witnessed a ground-breaking growth in the use of digital images and their applications in the modern society. Keywords: digital images, idct authentication cosine transforms, forgery detection, image forensics, images splicing, local pattern binary, support vector machines, wavelet transforms.
Related Work There are several forensic approaches to image manipulation detection and, commonly, these approaches could be divided into: intrusive or active and non-intrusive or passive approaches [ 4 ]. In social idct authentication networks where it is sufficient to verify if an image is original or manipulated, learning-based methods are used due to its great capacity to classify large datasets at a reduced cost of time and resources. Block-based methods are useful for presenting evidence in courtrooms or insurance claims. Their biggest disadvantage is the consumption of time and resources, which makes them unsuitable for applications such as social networks, where a large amount of images is shared every day.
Table 1 Main aspects of related previous works.The DirectX VA interface supports various ways of handling low-level inverse discrete-cosine transform (IDCT). There are two fundamental. Fixed-Point 8x8 IDCT and DCT MPEG doc#: NDate: July Author: Gary Sullivan.