A Visual Model-Based Perceptual Image Hash for Content Authentication
₹12500-37500 INR
Closed
Posted over 8 years ago
₹12500-37500 INR
Paid on delivery
Perceptual image hash has been widely investigated in an attempt to solve the problems of image content authentication and content-based image retrieval. In this paper, we combine statistical analysis methods and visual perception theory to develop a real perceptual image hash method for content authentication. To achieve real perceptual robustness and perceptual sensitivity, the proposed method uses Watson’s visual model to extract visually sensitive features that play an important role in the process of humans perceiving image content. We then generate robust perceptual hash code by combining image-block-based features and key-point-based features. The proposed method achieves a tradeoff between perceptual robustness to tolerate content-preserving manipulations and a wide range of geometric distortions and perceptual sensitivity to detect malicious tampering. Furthermore, it has the functionality to detect compromised image regions. Compared with state-of-the-art schemes, the proposed method obtains a better comprehensive performance in content-based image tampering detection and localization
The complete project will be delivered with Matlab GUI with the result of the below proposed .Visual Model compared with the other existing models
The user interface (GUI) will have the options to browse any image, adding noise to the image and checking image quality parameters for the filter on a button click.
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