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Watermarking Attacks and Tools
Published in Frank Y. Shih, Digital Watermarking and Steganography: Fundamentals and Techniques, 2017
In contrast to parallel projection, in perspective projection the parallel lines converge, the object size is reduced with increasing distance from the center of projection, and the nonuniform foreshortening of lines in the object occurs as a function of orientation and the distance of the object from the center of projection. All of these effects aid the depth perception of the human visual system, but the object shape is not preserved. An example of an attack using 30° rotation along the x-axis together with a perspective projection is shown in Figure 5.15.
Methods of Spatial Visualisation
Published in Ken Morling, Stéphane Danjou, Geometric and Engineering Drawing, 2022
Characteristic of parallel projection is that parallel lines projected on the plane of projection remain parallel. Furthermore, length ratios and division ratios also remain constant. Another advantage of parallel projection is that it does not produce any perspective foreshortening. Figure 4.3 depicts a parallel projection of a triangular face. While the plane of projection P1 is perpendicular to the projection lines sn, projection plane P2 is at an angle to the projectors. Both projected triangles will show the same length ratios.
Watermarking Attacks and Tools
Published in Frank Y. Shin, Digital Watermarking and Steganography, 2017
In contrast to parallel projection, in perspective projection the parallel lines converge, object size is reduced with increasing distance from the center of projection, and nonuniform foreshortening of lines in the object as a function of orientation and distance of the object from the center of projection occurs. All of these effects aid the depth perception of the human visual system, but the object shape is not preserved. An example of this attack using 30° rotation along an x-axis together with a perspective projection is shown in Figure 5.15.
A limit Kalman filter and smoother for systems with unknown inputs
Published in International Journal of Control, 2023
Grigorios Gakis, Malcolm C. Smith
It may be noted that the system with matrices , , , arises naturally when inverting the system (1)–(2) on pre-multiplying (2) by the left inverse of D (which is different to the left inverse in (19)) and substituting for in (1). This system features in the propagation steps (28)–(29) and in the update (25). The matrix Π is a parallel projection onto the range space of D along the null space of , and is a left annihilator of D (see (A17)), which means that (see (A18)). Hence, we may note that the component of the measurement vector in the range space of D does not contribute to the state update (23), whereas the component in the complement space does not contribute to the input update (25), so the two components of play distinct roles in the recursion.
Analysis of material variation in the design of knitted sportswear compression stockings to escort thermo-physiological comfort using linear regression
Published in The Journal of The Textile Institute, 2022
Adeel Abbas, Muhammad Sohaib Anas, Zeeshan Azam, Ruhma Naseer, Sikander Abbas Basra, Norina Asfand
Interface pressure between body and compression stocking’s fabric wasn’t significantly affected by main yarn material; however, number of inlay yarn covering filaments. P-values were less than 0.05 proving significance. Interaction plots explain behaviors over the parallel projection of lines, that is, parallel projection or no meeting point there will be no interaction between terms and vice versa. There was some interaction experienced between terms (Figure 9 (a)). However, the interactions compromised overall model’s adequacy. Statistically analyzing, the main effects plots indicated decreasing trend of compression via increasing number of covering filaments, and sorbtek showed the highest compression followed by nylon 6 and micro nylon (Figure 9 (b)).
Linear convergence rates for extrapolated fixed point algorithms
Published in Optimization, 2019
Christian Bargetz, Victor I. Kolobov, Simeon Reich, Rafał Zalas
We begin with the simultaneous cutter methods for which Pierra considered (3) in [10] for the extrapolated parallel projection method, where he established weak convergence of the sequence of iterates for , and . Moreover, under the bounded regularity of the family the convergence was shown to be in norm. The extrapolated parallel subgradient projection method () was introduced by Dos Santos in [11] in . Since then one can find many extensions in the literature. For example, Combettes [2,12] proposed the extrapolated method of parallel approximate projections (EMPAP), where each was assumed to be the projection onto a closed and convex superset and for some . The method was shown to converge weakly under additional regularity of the approximate projections, that is, . Norm convergence, as in [10], required bounded regularity of the family . Recently, Zhao et al. [4] have proved that EMPAP converges linearly whenever the family of the sets is assumed to be boundedly linearly regular.