## 1 Introduction  
Spatial self-organizing patterns (SOP) can be effectively exploited for hiding and transmitting secret digital images. A digital fingerprint image is used as the initial condition for the evolution of a pattern in a model of reaction-diffusion cellular automata [1]. A secure digital image communication scheme based on patterns evolving in a Beddington-DeAngelis-type predator-prey model with self- and cross-diffusion is proposed in [2]. Considerations on hardware implementation of image steganography based on reaction diffusion models are presented in [3]. SOP induced by evolutionary spatial \(2\times 2\) games are exploited for hiding and transmitting secret visual information in [4]. Competitively and non-diffusively coupled non-linear maps are used for hiding secret visual information in [5].  
However, above-mentioned pattern formation algorithms do exhibit a number of drawbacks in secret image communication applications. The self-organized pattern produced in a model of reaction-diffusion cellular automata [1] clearly resembles the initial fingerprint image and cannot be considered as an image hiding algorithm. At least 10,000 time forward iterations are required for the formation of an interpretable pattern produced by the reaction-diffusion model in [2,3]. The inversion of a single pixel in the initial random image does not result into any changes in the self-organized pattern produced by the communication algorithm proposed in [4]. Self-organized patterns produced by competitively and non-diffusively coupled non-linear maps [5] are originated by wave propagation in isotropic media, what predetermines a rather low complexity of the pattern structure.  
The main objective of this paper is to develop a computationally effective visual communication scheme which could preserve the security of the communication, but minimize all previously-mentioned drawbacks. It is well known that patterns produced by the atrial fibrillation (AF) model are originated from complex rules of self-organization and wave propagation in anisotropic media. The ability to exploit this complex pattern formation phenomenon in a digital image communication scheme is the main goal of this paper.  
Atrial muscle is comprised from myocytes that form the primal structure of the tissue. Observable patterns formed by myocytes are not regular and conform to complex self-organizing rules as proposed in [6,7]. Cells within this structure are coupled mainly by longitudinal (end-to-end) connections rather than latitudinal (side-by-side) connections thus resembling a cable-like signal transmission [6,8]. Conditions such as fibrosis and scarring processes can weaken and damage the connections [6], change and adjust the network of functioning cells [9,10].  
The whole interaction of cells within the network can be modeled as proposed in [11]. Longitudinal (end-to-end) signals are always transmitted, whereas latitudinal (side-by-side) signals are transmitted only with a probability \(\
u\). This non-symmetrical coupling corresponds to the physical organization of cable-like transmissions. As a simplification, the structure can be presented as a flat entity because the wall of the atrial muscle is relatively thin [8].  
This paper is organized as follows. The model of the system is presented in Section 2; the formation of SOP is discussed in Section 3. A communication scheme based on SOP in the AF model is presented in Section 4; the sensitivity of the proposed communication scheme to perturbations of its parameters is discussed in Section 5; Concluding remarks are given in the final section.