Competitive Swarm Improved Invasive Weed Optimization-Based Secret Sharing Scheme for Visual Cryptography

ENHANCING home security through visual CRYPTOGRAPHY

Prediction of pleural invasion in lung cancer is crucial in planning appropriate operating procedures and can be assessed using dynamic chest radiography (DCR). However, this assessment is negatively affected by rib shadows in conventional images. The purpose of this study was to develop a deep learning-based bone suppression technique for DCR in various projection directions. Twenty breathing XCAT phantoms with lung tumors and a pair of phantoms consisting only of bone structures were generated. The XCAT phantoms were virtually projected from six directions, resulting in 54000 multidirectional chest X-ray images and were used for training a pix2pix model to estimate bone images from original images. Bone suppression (BS) images were created by subtracting the bone images from the original images and then evaluated based on the peak signal to noise ratio (PSNR), structural similarity index measure (SSIM), and Fréchet Video Distance (FVD). Clinical cases were processed using the trained model as well. Furthermore, lung tumors on the original and BS images were tracked using OpenCV template matching, and the tracking accuracy was compared. The PSNR, SSIM, and FVD were 0.9966, 52.20 and 136.9, respectively. In the visual evaluation, we confirmed the effect of BS without temporal fluctuation of pixel values in both the resulting images of the XCAT phantom and real patients. Furthermore, precise tracking of the targeted tumor was achieved on the resulting BS images even in oblique directions, without any interruption from the rib shadows. These results indicate that our proposed method can effectively reduce bone shadows as well as temporal variations in the effect of bone suppression.

In recent years most of researcher’s has done tremendous work in the field of medical image applications such as Magnetic Resonance Imaging (MRI), Ultra Sound, CT scan but still there are many research and experiments in medical imaging field and diagnosing of human health by Health Care Institutes. There is a growing interest for medical imaging de-noising as a hot area of research and also imaging equipment as a device. It is used for better image processing and highlighting the important features. These images are affected with random noise during acquisition, analyzing and Transmission process. This results in blurry image visible in low contrast. Wavelet transforms have effective method to separate the noise from the original medical image by using threshold techniques without affecting the important data of an image. Wavelet transform enables us to use the forward wavelet transform to represent sub-band of the original image in decomposition process then reconstructing this sub band coefficients to original image using inverse wavelet transform. In this work, the quality of medical image has been evaluated using filter assessment parameters like Variance, standard deviation, the squared difference error between original medical image & de-noised image (MSE) and the ratio between original image & noisy image. From numerical results, we can see that the algorithm is efficient de-noising of noisy medical image. When, investigating with Baye’s threshold techniques it achieved the Best value of peak signal to noise ratio (PSNR). For best medical image de-noising, the wavelet based de-noising algorithm has been investigated and results of Baye’s techniques and hard & soft threshold methods have been compared.

For preserving the security of data there has been tremendous research areas evolved and explored since few years. Cryptography is seen to be the dominant strategy in the information security domain. To differentiate security of multimediadata, visual cryptography is seen as the prominent way for data confidentiality and secrecy of information being distributed. The mechanism of visual cryptography is widely used approach which encrypts the secrete image into the many meaningless share images and decodes by stacking some or all shares by human visual system. There are many methods presented for visual cryptography with their own advantages and disadvantages.. Over the years , in visual cryptography the scope of research mainly focused on developing techniques on grayscale , halftone , color visual cryptography, region incrementing visual cryptography, minimization of pixel expansion , multiple secret sharing and cheating prevention in visual cryptography. Recently new cheating–preventing scheme has been found whichis advantageous over a combined approach of two general VC codebooks. This method resulted into number of advantages such as computation cost is low; multi factor cheating detection is involved etc. However, we identified two research problems such as 1) there is no efficient generic method of generating (k,n) codebooks with minimizing the pixel expansion, 2) it is impractical and time-consuming to stack three or four shares. Therefore in this project our aim is to extend this hybrid codebook based method with goal of overcoming above two listed limitations. We are presenting the efficient approach for codebooks generation with less timing consuming while decryption. Keywords—Contrast,Share,Stacking,Pixel expansion.

A highly robust and secure image watermarking based on classification and visual cryptography

The world has become very much dependent on electronic devices and internet with the advancement of new technologies. So, security is also becoming a very vital issue as we share all our details through different electronic mediums to internet. Cryptography is a well known technique of hiding secret data. Visual Cryptography (VC) is a special type of cryptography where we can securely transmit secret data over different transmission mediums. Various visual cryptography schemes have been formulated to carry out the secure transmission of images efficiently. Visual Cryptography provides techniques to share an image efficiently over various internet services. In visual cryptography an image is broken into a number of share images which are later stacked upon to generate the original image. Out of various schemes some have shown very promising results with or without a small increase in the final image dimension which is also referred as pixel expansion. The proper alignment of the distributed shares reveals the original secret image. In this paper we provide a state-of-the-art review and analysis of the several existing schemes of Visual Cryptography.

Wavelet is one method that can be used as a step to recognition an individual . Wavelet is used to perform an image feature extraction . In the process of image texture analysis , showed the value of the coefficients of a wavelet . The magnitude of the coefficients obtained using wavelet feature extraction is influenced by several factors . Besides affected by the type of wavelet used , is also influenced by the magnitude of the wavelet decomposition level of itself. In the wavelet is known as the wavelet energy retention , which means the number of retained energy after undergoing a process of decomposition and cutting coefficients . During the decomposition process , the calculation for texture analysis is often a constraint . In order for the current calculation lighter texture analysis , necessary to the process of cutting coefficients based on the retention factor of the wavelet coefficients . Based on these issues , created a program to analyze the influence of variations in the level of wavelet decomposition and coefficient of variation coefficient of cutting a cut on the image . The object of this final project is 30 iris image that has been converted into polar form presented . Having experienced the process of cutting coefficients , to prevent the image of the reverse transformation has a big difference to the original image , in this study was calculated Mean Square Error ( MSE), Peak Signal to Noise Ratio ( PSNR), and Euclidean distance to determine the level of similarity of image input and output images . The Highest values of Retention ​, MSE and the Euclidean distance is obtained at the level of decomposition of 1 and the lowest at the level of decomposition 6 . While the truncated coefficient and PSNR values ​​obtained at the highest level of decomposition of 6 and the lowest level of decomposition of 6 . The variation coefficient of pieces , value retention and highest PSNR obtained at koefsien piece 5 and the lowest coefficient of 50 pieces . While the coefficient value is truncated , MSE and the highest Euclidean distance is obtained at koefsien pieces 50 and the lowest coefficient of 5 pieces . Keywords: iris, texture analysis, Haar wavelet transform, MSE, PSNR, E uclidean distance

Prior research studies have shown that the peak signal to noise ratio (PSNR) is the most frequent watermarked image quality metric that is used for determining the levels of strength and weakness of watermarking algorithms. Conversely, normalised cross correlation (NCC) is the most common metric used after attacks were applied to a watermarked image to verify the strength of the algorithm used. Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. This paper considers this issue to determine the threshold values of these two parameters in reflecting the amount of strength and weakness of the watermarking algorithms. We used our novel watermarking technique for embedding four watermarks in intermediate significant bits (ISB) of six image files one-by-one through replacing the image pixels with new pixels and, at the same time, keeping the new pixels very close to the original pixels. This approach gains an improved robustness based on the PSNR and NCC values that were gathered. A neural network model was built that uses the image quality metrics (PSNR and NCC) values obtained from the watermarking of six grey-scale images that use ISB as the desired output and that are trained for each watermarked image’s PSNR and NCC. The neural network predicts the watermarked image’s PSNR together with NCC after the attacks when a portion of the output of the same or different types of image quality metrics (PSNR and NCC) are obtained. The results indicate that the NCC metric fluctuates before the PSNR values deteriorate.

The reconstructed image of probabilistic visual cryptography (VC) is inevitably accompanied by the loss of secret image information and degradation of visual quality. Since halftone technique can realistically simulate grayscale continuous tone image with a binary image, in this paper, by combining VC sharing with grayscale image halftone technique, we propose a probabilistic VC scheme for grayscale image using EDBS (Efficient Direct Binary Search) to improve the quality of the reconstructed image. The probabilistic VC sharing is adopted into the EDBS halftone process, and the reconstructed image is taken as the optimization object. Through local optimizations and global iterations, the optimal reconstructed image is finally achieved under the established optimization strategy. Theoretically the proposed scheme possesses the same security strength as the traditional VC and experimentally the comparative analysis verifies the effectiveness of this scheme.

광을 이용하여 암호화를 하는 경우는 위조 및 복제의 방지를 위하여 세기성분보다는 위상성분을 이용하여 주로 암호화를 하고 있다. 그러나 위상정보를 검출할 수 있는 장비가 개발된다면 정보를 유출 당할 수 있는 위험이 있다. 이러한 위험을 줄이기 위해 본 논문에서는 가상 위상영상을 이용하고 또한 정보를 다수가 공유할 수 있도록 시각 암호화(visual cryptography) 방법을 이용하여 정보를 보다 안전하게 보관하고 공유하는 시스템을 제안하였다. We propose an encryption method using visual cryptography and virtual phase images. In the encryption process, the original image is shared by virtual images and the decryption key image. We multiply the virtual phase images with each complex image, which has the constant value of its sum after performing the phase modulation of the virtual images and the decryption key. The encryption cards are made by Fourier transforming the multiplied images. It is possible to protect information about the original image because the cards do not have any information from the original image. To reconstruct the original image, all the encryption cards are placed on each path of a Mach-Zehnder interferometer and then the lights passing through them are summed. Since the summed image is inverse Fourier transformed by a Fourier lens, the phase image is multiplied with the decryption key and the output image is obtained in the form of intensity on the CCD plane. Computer simulations show a good performance of the pro-posed optical security system.

This paper presents a method to hide three binary images in a grayscale image with same resolution. Pseudo Random Number Generator(PRNG) produces the random numbers that rearranges the binary values. PRNG algorithm is unique and the strength of random numbers generated are equal to random numbers generated without a seed value. Each binary image pixel values are rearranged through three random number series and it is hidden in a grayscale image through Ultra Unique Numbers (UUN). By comparing both concealed image and original image, modification among the image is identified. To identify concealed secret binary information in a grayscale image at the destination, UUN is reapplied. PRNG is used to rearrange the binary values for transforming the binary images. The main aim of this paper is to increase the embedding capacity of carter image without degrading the quality of the secret information with high Peak Signal Noise Ratio(PSNR).

With the development of smart devices and networks, security and privacy protection have become significantly important. Numerous encryption algorithms have been invented to transmit confidential data or to protect user privacy. However, as most of them need complicated computing, sometimes they may not be the best way to encrypt certain types of data. Visual cryptography is a unique approach that is different from other kinds of cryptography as it does not need any mathematical calculation, but only relies on human vision for decryption. It was first proposed by Naor and Shamir. This paper selects two methods of visual cryptography, black-and-white image secret sharing and color image secret sharing. The paper first introduces the concept of the two methods, then summarizes the disadvantages of the two original algorithms and gives several improvements. Finally, provide examples of applications. The simple operations and decryption conditions make visual cryptography quite promising for future applications.

By splitting a picture into many parts, which, when reassembled, disclose the original image without requiring complicated math, visual cryptography is a strong method for protecting visual information. Problems with pixel enlargement, decreased picture quality, and restricted access structures are common with traditional visual cryptography techniques. Our proposed improved visual cryptography approach incorporates pixel-wise operations and critical access structures to solve these challenges and increase flexibility, picture quality, and security. To reconstruct a picture, our technique calls for building visual cryptographic shares based on critical access structures that specify the exact combinations of shares needed. In order to maintain the image's resolution and reduce pixel expansion, we use pixel-wise processes. By improving the peak signal-to-noise ratio (PSNR) by up to 20% compared to conventional approaches, experimental data show that our strategy greatly improves picture quality. In addition, the suggested approach guarantees that individual shares do not disclose any information on the original picture, thereby maintaining high security requirements. Finally, it is clear that the enhanced visual cryptographic system is well-suited for a wide range of uses in safe communications and data security due to its strong solution for secure picture sharing, increased picture quality, and adjustable access control.

A simple and efficient watermark method is proposed in this paper. The watermark method is an excellent technique to protect the copyright ownership of a digital image. The proposed watermark method is built up on the concept of visual cryptography. According to the proposed method, the watermark pattern does not have to be embedded into the original image directly, which makes it harder to detect or recover from the marked image in an illegal way. It can be retrieved from the marked image without making comparison with the original image. The notary also can off-line adjudge the ownership of the suspect image by this method. The watermark pattern can be any significant black/white image that can be used to typify the owner. Experimental results show that the watermark pattern in the marked image has good transparency and robustness. By the proposed method, all the pixels of the marked image are equal to the original image.

Biometric Cryptography is the biometric tokenization used for authentication with public-key infrastructure (PKI). In particular, biometric cryptography provides the convenience of authentication via fingerprint, face, eye, voice, palm, etc. - with none of the risks posed by having the biometrics take the form of a shared secret. With comfort, biometric verification gives more security than as it were conventional cryptography-based confirmation. Since biometric highlights of each human being are distinctive from each other, that makes it difficult to get to in an unauthorized way and it jams the privacy at the time of verification since there's no plausibility of snooping. In this manner, these days the utilization of biometric-based confirmation has expanded and utilized in versatile, portable workstation, and numerous other gadgets are utilizing biometric-based verification and biometric information stored in biometric gadgets and programmers are exceptionally shrewd they can render biometric information, can take it, and not at all like username or password biometric information can not alter, due to unique feature of biometrics. It implies, compromising biometric information will be until the end of life, and programmers can take advantage of it, so the security of biometric information is a vital issue. This paper gives some idea about cryptography methods that are capable to secure biometric data and we have presented four cryptography methods which are Biometric Encryption, Blockchain, Cancelable biometrics, and Visual cryptography. This paper also provides some challenges, issues in biometric, and future direction.