Image Hiding Scheme with Modulus Function and Dynamic Programming Strategy on Partitioned Pixels",

[[abstract]]In this paper, we shall propose a novel image-hiding scheme. Our new scheme classifies the host image pixels into two groups of pixels according to the pixel values. For each group of pixels, the corresponding secret pixel values go through an optimal substitution process and are transformed into other pixel values by following the dynamic programming strategy. Then, we can embed the transformed pixel values in the host pixels by using the modulus functions and obtain the stego-image. Extensive experimental results demonstrate that our new method is capable of offering better stego-image quality than a number of well-accepted schemes

Application of Stochastic Diffusion for Hiding High Fidelity Encrypted Images

Cryptography coupled with information hiding has received increased attention in recent years and has become a major research theme because of the importance of protecting encrypted information in any Electronic Data Interchange system in a way that is both discrete and covert. One of the essential limitations in any cryptography system is that the encrypted data provides an indication on its importance which arouses suspicion and makes it vulnerable to attack. Information hiding of Steganography provides a potential solution to this issue by making the data imperceptible, the security of the hidden information being a threat only if its existence is detected through Steganalysis. This paper focuses on a study methods for hiding encrypted information, specifically, methods that encrypt data before embedding in host data where the ‘data’ is in the form of a full colour digital image. Such methods provide a greater level of data security especially when the information is to be submitted over the Internet, for example, since a potential attacker needs to first detect, then extract and then decrypt the embedded data in order to recover the original information. After providing an extensive survey of the current methods available, we present a new method of encrypting and then hiding full colour images in three full colour host images with out loss of fidelity following data extraction and decryption. The application of this technique, which is based on a technique called ‘Stochastic Diffusion’ are wide ranging and include covert image information interchange, digital image authentication, video authentication, copyright protection and digital rights management of image data in general

Information Hiding using LSB Technique based on Developed PSO Algorithm

Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most efficient and speed. An agents population is used in determining process of a required goals at search space for solving of problem. The (Dev.-PSO) algorithm is applied to different images; the number of an image which used in the experiments in this paper is three. For all used images, the Peak Signal to Noise Ratio (PSNR) value is computed. Finally, the PSNR value of the stego-A that obtained from blue sub-band colo is equal (44.87) dB, while the stego-B is equal (44.45) dB, and the PSNR value for the stego-C is (43.97)dB, while the vlue of MSE that obtained from the same color sub-bans is (0.00989), stego-B equal to (0.01869), and stego-C is (0.02041). Furthermore, our proposed method has ability to survive the quality for the stego image befor and after hiding stage or under intended attack that used in the existing paper such as Gaussian noise, and salt & pepper noise

Secure digital documents using Steganography and QR Code

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonWith the increasing use of the Internet several problems have arisen regarding the processing of electronic documents. These include content filtering, content retrieval/search. Moreover, document security has taken a centre stage including copyright protection, broadcast monitoring etc. There is an acute need of an effective tool which can find the identity, location and the time when the document was created so that it can be determined whether or not the contents of the document were tampered with after creation. Owing the sensitivity of the large amounts of data which is processed on a daily basis, verifying the authenticity and integrity of a document is more important now than it ever was. Unsurprisingly document authenticity verification has become the centre of attention in the world of research. Consequently, this research is concerned with creating a tool which deals with the above problem. This research proposes the use of a Quick Response Code as a message carrier for Text Key-print. The Text Key-print is a novel method which employs the basic element of the language (i.e. Characters of the alphabet) in order to achieve authenticity of electronic documents through the transformation of its physical structure into a logical structured relationship. The resultant dimensional matrix is then converted into a binary stream and encapsulated with a serial number or URL inside a Quick response Code (QR code) to form a digital fingerprint mark. For hiding a QR code, two image steganography techniques were developed based upon the spatial and the transform domains. In the spatial domain, three methods were proposed and implemented based on the least significant bit insertion technique and the use of pseudorandom number generator to scatter the message into a set of arbitrary pixels. These methods utilise the three colour channels in the images based on the RGB model based in order to embed one, two or three bits per the eight bit channel which results in three different hiding capacities. The second technique is an adaptive approach in transforming domain where a threshold value is calculated under a predefined location for embedding in order to identify the embedding strength of the embedding technique. The quality of the generated stego images was evaluated using both objective (PSNR) and Subjective (DSCQS) methods to ensure the reliability of our proposed methods. The experimental results revealed that PSNR is not a strong indicator of the perceived stego image quality, but not a bad interpreter also of the actual quality of stego images. Since the visual difference between the cover and the stego image must be absolutely imperceptible to the human visual system, it was logically convenient to ask human observers with different qualifications and experience in the field of image processing to evaluate the perceived quality of the cover and the stego image. Thus, the subjective responses were analysed using statistical measurements to describe the distribution of the scores given by the assessors. Thus, the proposed scheme presents an alternative approach to protect digital documents rather than the traditional techniques of digital signature and watermarking

Accelerated volumetric reconstruction from uncalibrated camera views

While both work with images, computer graphics and computer vision are inverse problems. Computer graphics starts traditionally with input geometric models and produces image sequences. Computer vision starts with input image sequences and produces geometric models. In the last few years, there has been a convergence of research to bridge the gap between the two fields. This convergence has produced a new field called Image-based Rendering and Modeling (IBMR). IBMR represents the effort of using the geometric information recovered from real images to generate new images with the hope that the synthesized ones appear photorealistic, as well as reducing the time spent on model creation. In this dissertation, the capturing, geometric and photometric aspects of an IBMR system are studied. A versatile framework was developed that enables the reconstruction of scenes from images acquired with a handheld digital camera. The proposed system targets applications in areas such as Computer Gaming and Virtual Reality, from a lowcost perspective. In the spirit of IBMR, the human operator is allowed to provide the high-level information, while underlying algorithms are used to perform low-level computational work. Conforming to the latest architecture trends, we propose a streaming voxel carving method, allowing a fast GPU-based processing on commodity hardware

Connected Attribute Filtering Based on Contour Smoothness

A new attribute measuring the contour smoothness of 2-D objects is presented in the context of morphological attribute filtering. The attribute is based on the ratio of the circularity and non-compactness, and has a maximum of 1 for a perfect circle. It decreases as the object boundary becomes irregular. Computation on hierarchical image representation structures relies on five auxiliary data members and is rapid. Contour smoothness is a suitable descriptor for detecting and discriminating man-made structures from other image features. An example is demonstrated on a very-high-resolution satellite image using connected pattern spectra and the switchboard platform