Abstract Natural face images are both content and context-rich, in the sense that they carry significant immersive information via depth cues embedded in the form of self-shadows or a space varying blur. Images of planar face prints, on the other hand, tend to have lower contrast and also suppressed depth cues. In this work, a solution is proposed, to detect planar print spoofing by enhancing self-shadow patterns present in face images. This process is facilitated and siphoned via the application of a non-linear iterative functional map, which is used to produce a contrast reductionist image sequence, termed as an image life trail. Subsequent images in this trail tend to have lower contrast in relation to the previous iteration. Differences taken across this image sequence help in bringing out the self-shadows already present in the original image. The proposed solution has two fronts: (i) a calibration and customization heavy 2-class client specific model construction process, based on self-shadow statistics, in which the model has to be trained with respect to samples from the new environment, and (ii) a subject independent and virtually environment independent model building procedure using random scans and Fourier descriptors, which can be cross-ported and applied to new environments without prior training. For the first case, where calibration and customization is required, overall mean error rate for the calibration-set (reduced CASIA dataset) was found to be 0.3106%, and the error rates for other datasets such OULU-NPU and CASIA-SURF were 1.1928% and 2.2462% respectively. For the second case, which involved building a 1-class and 2-class model using CASIA alone and testing completely on OULU, the error rates were 5.86% and 2.34% respectively, comparable to the customized solution for OULU-NPU.

In natural photography, defects in camera imaging pipeline often result in some form of colour noise or distortion. Nature of this distortion is generally intertwined with scene dependent variables such as positioning, intensity and composition of light source and local object colour reflectivity. One such defect is called purple fringing aberration (PFA). PFA problems are of two types, one of which corresponds to a localised fringing effect near high contrast zones (termed as Isolated PFA or IS‐PFA) and the second which corresponds to a widespread semi‐transparent purple haze over a large part of natural scene (termed as complex PFA or C‐PFA). Much of the PFA‐correction solutions have been driven towards IS‐PFA and very little towards C‐PFA. Based on a premise that in C‐PFA, green channel is heavily suppressed and noisy, while colour information in red and blue channels are largely conserved, authors propose a green‐channel compensation algorithm for restoring true natural colours in fringe affected region. To correct white‐tuft produced by proposed compensation algorithm, they also devise a suitable localised luminance adaptation procedure to equalise perceived changes in luminance profile. Comparisons with state‐of‐the‐art methods devised to combat this purple haze effect yield promising results for a majority of test cases.

A set of semi-fragile watermarks Wfr= {V1, V2,.., Vv} can be used as building blocks for constructing any digital fingerprint. One such family, is obtained by modulating the sign bits alone of selective DCT-AC coefficients, where, each Vjrepresents the positions of a disjoint subset of modulated coefficients. We show that a linear collusion of Kjand '0' its erasure. By design, each block Vjis unperturbed by specific collusion patterns and so by facilitating complementary coverage of each newly added block Vj+1, a compact anti-collusion code (ACC)for tracking linear collusions can be constructed.

This paper provides a tutorial and survey of digital fingerprinting and video scrambling algorithms based on partial encryption. Necessary design tradeoffs for algorithm development are highlighted for multicast communication environments. We also propose a novel architecture for joint fingerprinting and decryption that holds promise for a better compromise between practicality and security for emerging digital rights management applications.