Processing real-world imagery with FACADE-based approaches

Abstract

This paper considers the processing of realworld imagery in the so-called Form-And-Color-And-DEpth (FACADE) framework, which features some superior mechanisms of the human vision system (HVS). FACADE framework was originally proposed by Grossberg et al. as an integrative model of the HVS to illustrate the possible procedures for visual perception of shape (the boundary contour), surface (luminance and color), and binocular depth. As a simplified, reasonable and mathematically full-fledged approach to the HVS, we saw FACADE as a promising infrastructure through which to construct a powerful image processing engine. However, in our attempts to use the approach in its original modality, to deal with real-world imagery, we found it to be inefficient and non-robust.

After re-introducing the model hierarchy and illustrating the involved cell dynamics of the FACADE framework, this paper reveals the crucial issues that lead to the deficiency and accordingly present our substitutive solutions by incorporating the mechanisms of anisotropic spatial- and diffusive orientational-competition to make the HVS-featured model efficient and robust. A computer system based on the improved FACADE engine has been implemented and tested not only with illustrative images to highlight the model characteristics, but also with some real-world imagery in both monocular and binocular situations, thereby demonstrating the ability of the FACADE-based image processing approach featuring the HVS.

Key words： visual perception; human vision system (HVS); Form-And-Color-And-DEpth (FACADE) framework; real-world imagery

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