Performance of Biometric Quality Measures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image quality assessment based on a degradation model
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image information and visual quality
IEEE Transactions on Image Processing
A two-stage quality measure for mobile phone captured 2D barcode images
Pattern Recognition
Document authentication using graphical codes: impacts of the channel model
Proceedings of the first ACM workshop on Information hiding and multimedia security
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Document authentication is the process by which a unique identifier is assigned to each version of a printed document and is verified via an inspection procedure. One type of approach that has proven successful involves printing overt color-tile security deterrents, which can be scanned and analyzed to provide authenticity. For a variety of reasons discussed herein, it is advantageous to estimate whether or not a printed deterrent will authenticate without invoking the actual authentication process. Several algorithms are presented to predict the outcome of the authentication process. The area-over-the-curve (AOC) statistic is one of the tools used to characterize how well each candidate algorithm estimates authentication performance in the presence of distortions introduced via different print+scan paths. A surprising but useful result is that a no-reference metric yields the best performance: the AOC is approximately half that of all other tested methods, and is over five times smaller than the AOC achieved by state-of-the-art algorithms SSIM and VIF.