Edge Detection Algorithm Inspired by Pattern Formation Processes of Reaction-Diffusion Systems

This paper presents a quick review of reactiondiffusion systems and the application of a discretized version of a reaction-diffusion system to edge detection in image processing. A reaction-diffusion system refers to a system consisting of diffusion processes coupled with reaction processes. Several reaction-diffusion systems exhibit pattern formation processes, in which the systems self-organize spatio-temporal patterns of target and spiral waves propagating in two-dimensional space. In addition, some of the systems having strong inhibitory diffusion self-organize stationary patterns; the Turing pattern is one of the typical examples of the stationary patterns observed in reaction-diffusion systems under strong inhibitory diffusion. We have previously found that the discretized version with strong inhibition has a mechanism detecting edges from an image intensity distribution. The mechanism divides an image intensity distribution into brighter or darker intensity areas with a threshold level, and organizes pulses along edges of the divided areas. By searching an output distribution of the version for pulses, we can achieve edge detection. However, since the threshold level is usually fixed at a constant value in the version, the mechanism is not applicable to gray level images. Thus, this paper furthermore proposes an edge detection algorithm consisting of two pairs of the version with a variable threshold level. We apply the edge detection algorithm and a representative algorithm proposed by Canny to several artificial and real images in order to confirm their performance.

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