Effects of deficit irrigation on cotton growth and water use efficiency: A review.

Cotton is one of the most important crops in the world. With the increasing scarce of global water resources, irrigation water will become a major limiting factor in cotton production. Deficit irrigation is an irrigation method which consumes less water than the normal evapotranspiration of crops. It is an effective water-saving method due to improved water use efficiency without sacrificing cotton yield and fiber quality. We summarized the effects of deficit irrigation on the growth and water use efficiency of cotton. The results showed that deficit irrigation promoted the transformation from vegetative growth to reproductive growth, reduced plant height, leaf area, and total biomass of cotton, and subsequently improved the harvest index, stem diameter and water use efficiency. Finally, based on the current research and combined with cotton production reality, the application and future development of deficit irrigation were proposed, which might provide theoretical guidance for the sustainable development of cotton plantation in arid areas.

Image inpainting-based behavior image secret sharing.

The polynomial-based image secret sharing (ISS) scheme encodes a secret image into n shadows assigned to n participants. The secret image with high resolution is decoded by Lagrange interpolation when collecting any k or more shadows. Thus, ISS is used in applications such as distributive storage in the cloud, digital watermarking, block chain, and access control. Meaningful shadows are significant in ISS because meaningful shadows decrease the suspicion of image encryption and increase the efficiency of shadow management. Generally, previously meaningful ISS schemes were achieved through embedding the shadows into cover images using information hiding techniques and suffer from large pixel expansion and complex decoding procedure. Digital image processing, such as inpainting (texture synthesis), is a standard technique in multimedia applications. It will be highly significant if ISS can be performed in the processing of a normal digital image processing technique. Generally, the encoding method of an ISS scheme entails the use of a mathematical function that is sensitive to any slight change in the ISS output; therefore, the development of a method for performing the ISS procedure and simultaneously achieving image processing behavior is a key challenge. In this paper, we exploit the behavior ISS (BISS) and realize an image inpainting-based BISS scheme for the (k, n) threshold. Using screening operations, a secret image is encoded into the pixels of cover images by polynomial-based ISS in the processing of inpainting shadows to obtain meaningful shadows similar to the input cover images. In addition, the secret image can be losslessly decoded by Lagrange interpolation when collecting any k or more shadows. Experiments are given to confirm the efficiency of the scheme.

A compressed secret image sharing method with shadow image verification capability.

Secret image sharing (SIS) is an important research direction in information hiding and data security transmission. Since the generated shadow images (shares) are always noise-like, it is difficult to distinguish the fake share from the unauthorized participant before recovery. Even more serious is that an attacker with a fake share can easily collect shares of other honest participants. As a result, it is significant to verify the shares, before being taken out for recovery. Based on two mainstream methods of SIS, such as polynomial-based SIS and visual secret sharing(VSS), this paper proposed a novel compressed SIS with the ability of shadow image verification. Considering that the randomness of the sharing phase of polynomial-based SIS can be utilized, one out of shares of (2, 2)-threshold random-grid VSS is embedded into all shares of polynomial-based SIS by a XOR operation as the verification information, while the other binary share is private for verification. Before recovery, each participant must extract the binary share from the grayscale share to perform XOR operation with the private share, and the original binary image can be recovered only with the true share. The proposed scheme also has the characteristics of shadow image verification, pixel compression, loss tolerance and lossless recovery. Through experiments and comparative analysis of related research results, the effectiveness and advantages of the method are verified.

Multiple security anti-counterfeit applications to QR code payment based on visual secret sharing and QR code.

In this paper, we propose a novel mechanism for QR code security anti-counterfeit based on the fusion of visual secret sharing (VSS) and QR code (called VSSQR scheme), which can greatly improve the security of QR code payment. Due to different application scenarios, the background security anti-counterfeit application and the prospects security anti-counterfeit application are shown for QR code payment authentication. The basic idea of the two applications can be characterized as follows. First, two QR code shares that contain the information of the merchant can be generated based on VSSQR scheme with an original secret image. Second, the secret image can be revealed by stacking two QR code shares to obtain the original information. Finally, whether the stacking result is the same as the original secret image or not can determine the authenticity of QR code share used for payment. The analyses show the security of our method. The applications are conducted to show the effectiveness and practicability.