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Various Dimensions of Visual Cryptography
Published in Shivendra Shivani, Suneeta Agarwal, Jasjit S. Suri, Handbook of Image-Based Security Techniques, 2018
Shivendra Shivani, Suneeta Agarwal, Jasjit S. Suri
First of all, we must know what is a halftone image and how it is generated? Traditional visual cryptography schemes were based on binary secret images. Binary and halftone images both consist of only two intensities, one is for black and other is for white. But the appearance of each image is entirely different. A binary image may contain continuous clusters of black and white pixels withot having shades. Whereas halftone images are generated by the reprographic technique that simulates continuous/multitone images through the use of dots, varying either in size or in spacing, thus the image looks like a gray scale image. We can understand it by Figure 2.4, here (a) is the gray scale image of Lena which consists of 256 gray scale intensities. Figure 2.4 (b) is the binary version of the Figure 2.4 (a) which is achieved by the thresholding method. Figure 2.4 (c) is the halftone version of Figure 2.4 (a). We can see clearly that (c) is also made up of dots of only two intensities (black and white) with varying shapes and spacing. A halftone image creates an illusion of a gray scale image, hence it is useful in various applications.
Densitometry Measurement
Published in John G. Webster, Halit Eren, Measurement, Instrumentation, and Sensors Handbook, 2017
Halftone patterns are used in the printing industry to reproduce continuous-tone images using two levels of ink: either ink or no ink. Various gray levels are produced by printing a pattern of repetitive “dots” too small to be resolved by the unaided eye. Essentially, the size of the dots is varied to produce a gray scale. Halftone patterns to be measured may be transmitting or reflecting, monochrome or color. A number of standards for densitometry in the graphic arts have been approved or are under development [14]. These standards provide much practical guidance and are consistent with ISO 5. Densitometry in this field is an example of the basic mechanism by which the instrument operates—comparing the flux reaching the sensor with and without the sample in place. When the sample is a halftone, the flux reaching the sensor depends on the fractions of the area that are dense and clear. Adopting the notation of Ref. [13b] and assuming a transmitting sample, the measured density will be
Digital color halftones
Published in Sharma Gaurav, Digital Color Imaging Handbook, 2017
Charles Hains, Shen-Ge Wang, Keith Knox
A halftone is needed to display an image on media that cannot reproduce many levels or colors. The prime example of this is the print media. With the exception of a few continuous-tone desktop printers, the vast majority of printed material uses halftones to represent images. Today, those images are almost exclusively prepared digitally, with digital halftones. Most computer monitors display images in color and continuous tone but, because of bandwidth limitations, the very highest resolutions are shown with reduced numbers of colors. To display an image on a monitor with reduced colors requires color quantization and digital halftoning. Color quantization is discussed in a separate chapter.
An enhanced color visual cryptography scheme based on the binary dragonfly algorithm
Published in International Journal of Computers and Applications, 2022
Dyala R. Ibrahim, Rosni Abdullah, Je Sen Teh
As mentioned in Section 2, Hou introduced the first color VC scheme [19]. Although Hou introduced three different schemes for encrypting color images, we will only describe their third method which solves problems of the other two. A color image will first be decomposed into three halftone images (one for each color channel, cyan, magenta and yellow). Each halftone image is then decomposed into two, resulting in six temporary shares , , , , and . A colored halftone share is then obtained by combining three of these temporary shares (one from each color). Stacking the colored halftone share will lead to the recovery of the original colored image.
GPGPU-based randomized visual secret sharing (GRVSS) for grayscale and colour images
Published in International Journal of Computers and Applications, 2022
Raviraja Holla, Nikhil C. Mhala, Alwyn R. Pais
The Extract (Equation 4) is the function to extract the embedded data from the received share. This extract results in two sets of values and from even and odd share blocks respectively. These two sets are used to generate . The function Restore restores the original coefficient value as in Equation (5). Each block is de-quantized by multiplying the standard table shown in Figure 1 and then inverse DCT is applied to restore the original shares. Then random values in the range minimum to the maximum are embedded in the middle and its adjacent location, as shown in Figure 2. The shares when stacked recreates the original halftone image. However, the original image has values ranging from 0 to 255. So to estimate pixel values from the halftone image, the inverse halftone technique [29] is used. values are added at the respective locations of the halftone image to improve contrast. Then post-processing is done by applying the Wiener filter to alleviate noise effect [5].
Reflectance model for filament yarn composed of different color monofilaments
Published in The Journal of The Textile Institute, 2021
Yujuan Wang, Guangxue Chen, Wengang Li, Xuehui Gan, Jun Wang
As for the color mixing of ink, the classic models are Neugebauer equation (Hebert, 2014; Mazauric et al., 2017; Viggiano, 2018) and Clapper-Yule model (Clapper & Yule, 1953; Pottier et al., 2018; Wang, 2018). Based on these models, many advances have been made by researchers. Babaei et al. (2016) presented a thickness enhanced Clapper–Yule prediction model to generate full color images which after shrinking have colors as close as possible to the original colors. Mazauric et al. (2018) introduced a so-called ‘mean-path-defined Yule-Nielsen’ model for predicting the color of halftone prints in reflectance or transmittance modes, inspired by the Yule-Nielsen modified spectral Neugebauer model. Ke et al. (2014) proposed a new path branching Clapper-Yule prediction model of spectral reflectance based on the traveling probability and the path branching factor. Yet, these models usually only consider the propagation of light inside three-layer mediums (the air layer, the ink layer, and the paper layer). Moreover, most of these models need the refractive index of the medium, but it is difficult to accurately measure the refractive index of the filament in the visible spectrum range.