Image Hashing Algorithm Based on Mirror Flipping and a Three-Dimensional Space Angle

In order to make full use of image flipping information to get comprehensive image features and improve the distinguishing performance of hash algorithm, this paper proposes a new image hashing algorithm based on mirror flipping and a three-dimensional space angle. Firstly, the original image is preprocessed and then combined with mirror flipping image to obtain the new luminance component and opposite color components. Then, we combine new luminance component with the different sizes of structural elements to construct morphological features. The new opposite color components are used to construct a three-dimensional space. The angle between vectors formed by the pixels in the three-dimensional space is computed to construct the space angle features. Finally, the morphological features and space angle features are combined and disturbed to form the final hash sequence. Simulation results show that the algorithm has good security and tamper image recognition accuracy. Compared with some existing algorithms, it has better image classification performance and shorter computation time.

On spatial matchings: The first-in-first-match case

We describe a process where two types of particles, marked red and blue, arrive in a domain at a constant rate. When a new particle arrives into the domain, if there are particles of the opposite color present within a distance of 1 from the new particle, then, among these particles, it matches to the one with the earliest arrival time, and both particles are removed. Otherwise, the particle is simply added to the system. Additionally, particles may lose patience and depart at a constant rate. We study the existence of a stationary regime for this process, when the domain is either a compact space or a Euclidean space. In the compact setting, we give a product-form characterization of the stationary distribution, and then prove an FKG-type inequality that establishes certain clustering properties of the particles in the steady state.

Robust Image Hashing Based on Cool and Warm Hue and Space Angle

Image hashing has attracted more and more attention in the field of information security. In this paper, a novel hashing algorithm using cool and warm hue information and three-dimensional space angle is proposed. Firstly, the original image is preprocessed to get the opposite color component and the hue component H in HSV color space. Then, the distribution of cool and warm hue pixels is extracted from hue component H. Blocks the hue component H, according to the proportion of warm hue and cool hue pixels in each small block, combined with the quaternion and opposite color component, constructed the cool and warm hue opposite color quaternion (CWOCQ) feature. Then, three-dimensional space, opposite color, and cool and warm hue are combined to obtain the three-dimensional space angle (TDSA) feature. The CWOCQ feature and the TDSA feature are connected and disturbed to obtain the final hash sequence. Experimental results show that the proposed algorithm has good security and has better image classification performance and shorter computation time compared with some advanced algorithms.

The effect of some of spaces and sets of topology on the types of digital images

There is a growing interest in studying and improving the characteristics of images and objects in the e-commerce environment. Digital topology is concerned with dealing with the properties and features of two-dimensional (2D) or three-dimensional (3D) digital images such as borders, shapes, the intensity of illumination, and other characteristics. This paper aims to introduce and study new classes of fg-disconnected space and compactly fg-closed set, which could impact the brightness and brightness of the internal components of the types of color images, gray and binary. The paper also aims to find the effect of implementing fg-disconnected space and compactly fg-closed set to determine the brightness and brightness of the internal components of the types of color images, gray and binary. Each research plate contains 30 images of each type of image. Ten different images were chosen at the same time to be analyzed and executed using the proposed system based on MATLAB software. The study proved that higher brightness and light will disappear and delete the components of the image of any kind. This aimed to make the image white and opposite color, the greater darkness, and luminescence will make the picture color mysterious and turn to black.

Research on the Color-Difference Evaluation of Food Package Printing Matter Based on the Human Visual Characteristics

In order to improve for the inadequacy of traditional evaluation methods, this paper researched a kind of color-difference evaluation method for the food package printing matter based on human visual characteristics. Research method is as follow: the reference image and the target image were transformed to the opposite color space, and were dealt with the human eye Contrast Sensitive Function (CSF) spatial filter. The modified three opposite color component of images were transformed into the CIE XYZ space image after CSF spatial filtering processed; finally the image was transformed to the CIELAB space image. The color-difference of the target image was calculated according to color-difference formula. The color-difference result of image is the calculation result with human visual characteristics filtering processed; it combines subjective evaluation with objective evaluation. The research could provide practical and effective evaluation method for the field of food package printing matter.

Study on Correlation of Color Components Image in Different Color Spaces

Color image is an information substance with color components, among which exists correlation. In order to investigate the internal relevance of information in color image and to find out the dependence between them, to research the correlation of the color component image is significant. In order to investigate the relationship between the color space and the correlation of the component images, color spaces RGB/ LCH/ LAB/ OHTA/ YCC are selected and the correlation coefficients and cross correlations of the component images are computed and analyzed on MATLAB platform. The Result shows, that the statistical correlation coefficients of component images under RGB color space are the highest, while in OHTA color space the lowest are showed. The correlation coefficients under LAB and LCH are relative lower. In the opposite color spaces, the correlation coefficients of two opposite color components images are higher than the coefficients between the lightness and one of the opposite color component images. For the cross correlation of color component images, it shows a weak negative exponent relationship between pixel distance and cross correlation. The average cross correlation of component images in LCH space is obvious lower than in other spaces, while the levels of cross correlation in other spaces are similar. The relationship between cross correlation and color characteristics of image in RGB color space is closely, while in OHTA space, the difference of cross correlations among component images are usually small. In LCH space, the difference of cross correlations among component images is obvious, the cross correlation among chroma and the other components (lightness and hue) are much lower.

Task-relevant and Task-irrelevant Dimensions Are Modulated Independently at a Task-irrelevant Location

Single-cell and fMRI experiments indicate that task-relevant features are enhanced globally across the visual field (VF). Moreover, this global feature-based attention can spread to task-irrelevant features of the attended object. Here we ask whether a task-irrelevant feature, by virtue of being bound to a task-relevant feature, can also be enhanced at a task-irrelevant location. Specifically, we asked whether attending to the color of moving dots in one VF would influence the motion signal to colored moving dots in the other VF. Participants attended to either red or cyan dots, superimposed and moving in opposite directions. Critically, the color and motion of dots present in the opposite VF varied as a function of the attended dots such that they were either the same color/same direction, same color/opposite direction, opposite color/same direction, or opposite color/opposite direction as the attended dots. We found greater activity in ventral visual cortex when either the color or direction of motion matched the color or direction of motion at the attended location. Similar effects were found for direction of motion in human medial temporal/medial superior temporal cortex. Moreover, the color and motion effects did not interact in any region. Together, these results suggest that the coselection of an object's features modulates those features independently beyond the selected object.

CAN THE COLOR FORCE BE USED TO ACHIEVE FUSION?

We explore the possibility that the color force can be used to overcome the Coulomb barrier in fusion, If there are small deviations from exact color neutrality, large separations of color may occur when two elements of opposite color defects are mixed non-uniformly. In order to restore color neutrality locally, the strong color force polarizes the nuclei and brings them close enough to fuse. If palladium and deuterium are such elements, it is possible that all the recent cold fusion results are but different manifestations of the above process.