A Simple and Robust Gray Image Encryption Scheme Using Chaotic Logistic Map and Artificial Neural Network

A robust gray image encryption scheme using chaotic logistic map and artificial neural network (ANN) is introduced. In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. The plain image is divided into four subimages which are used for the first diffusion stage. The subimages obtained previously are divided into the square subimage blocks. In the next stage, different initial conditions are employed to generate a key stream which will be used for permutation and diffusion of the subimage blocks. Some security analyses such as entropy analysis, statistical analysis, and key sensitivity analysis are given to demonstrate the key space of the proposed algorithm which is large enough to make brute force attacks infeasible. Computing validation using experimental data with several gray images has been carried out with detailed numerical analysis, in order to validate the high security of the proposed encryption scheme

Multistability Analysis and Function Projective Synchronization in Relay Coupled Oscillators

Regions of stability phases discovered in a general class of Genesio−Tesi chaotic oscillators are proposed. In a relatively large region of two-parameter space, the system has coexisting point attractors and limit cycles. The variation of two parameters is used to characterize the multistability by plotting the isospike diagrams for two nonsymmetric initial conditions. The parameters window in which the jerk system exhibits the unusual and striking feature of multiple attractors (e.g., coexistence of six disconnected periodic chaotic attractors and three-point attraction) is investigated. The second aspect of this study presents the synchronization of systems that act as mediators between two dynamical units that, in turn, show function projective synchronization (FPS) with each other. These are the so-called relay systems. In a wide range of operating parameters; this setup leads to synchronization between the outer circuits, while the relaying element remains unsynchronized. The results show that the coupled systems can achieve function projective synchronization in a determined time despite the unpredictability of the scaling function. In the coupling path, the outer dynamical systems show finite-time synchronization of their outputs, that is, displaying the same dynamics at exactly the same moment. Further, this effect is rather general and it has a wide range of applications where sustained oscillations should be retained for proper functioning of the systems

Analysis and electronic circuit implementation of an integer- and fractional-order four-dimensional chaotic system with offset boosting and hidden attractors

In this paper, an integer- and fractional-order form of a four-dimensional (4-D) chaotic system with hidden attractors is investigated using theoretical/numerical and analogue methods. The system is constructed not through the extension of a three-dimensional existing nonlinear system as in current approaches, but by modifying the well-known two-dimensional Lotka-Volterra system. The equilibrium point of the integer-order system is determined and its stability analysis is studied using Routh-Hurwitz criterion. When the selected bifurcation parameter is varied, the system exhibits various dynamical behaviors and features including intermittency route to chaos, chaotic bursting oscillations and offset boosting. Moreover, the fractional-order form of the system is examined through bifurcation analysis. It is revealed that chaotic behaviors still exist in the system with order less than four. To validate the numerical approaches, a corresponding electronic circuit for the model in its integer and fractional order form is designed and implemented in Orcard-Pspice software. The Pspice results are consistent with those from the numerical simulations

Automating the clinical stools exam using image processing integrated in an expert system

International audienceBackground and objective: The diagnosis of intestinal parasitosis disease relies on physiological symptoms and stool examination. Often, few specialists are available, and manual stool exam is slow, prone to error, and can cause eye fatigue. Our aim was to design and implement a medical expert system that would be automated and helpful for diagnosis of human intestinal parasitosis.Methods: The system was developed based on a decision algorithm. A knowledge base was constructed through information gleaned from books and physicians with information pertaining to the disease. The user interacts with the system by answering questions. The symptoms information collected led to a microscopic examination of stools, which was run on the system to detect parasites. The paradigm for automated microscopic examination of stools consisted of a combined distance regularized level set evolution, automatically initialized by a circular Hough transform, and a trained neuro-fuzzy classifier. The neuro-fuzzy classifier was trained for analysis of twenty human intestinal parasites.Results: We combined the reasoning scheme of diagnosis and the automated clinical exam of stools in the same system. The parasites found in microscopic imagery confirmed the suspicious disease. The final recommendation of diagnosis was then completed, with appropriate proposed therapy. The system was evaluated with sixty cases of infection, and compared to the diagnosis of two expert doctors; we obtained fifty eight correct diagnoses, corresponding to a 96.6% accuracy.Conclusions: The proposed system is automated, since the parameters of segmentation, feature extraction and classification are set to be computationally guided by the type of suspicious parasite. The system is potentially an important contribution for medical healthcare assistance