The index of structural anisotropy is introduced, which serves as a measure of the fuzziness of growth-rate quantification. A discrete model of fish scale incremental pattern is proposed, which takes into account the incremental structure in 2D. This model is based on a representation of the fish scale pattern as a relay network, taking anisotropy in the form of discontinuities and convergences of incremental structural elements into account, and the widths of growth increments in different directions. The model is used to formalize procedures necessary for the quantification of fish scale growth rate. The capability of the model for analysing objects with similar structural attributes as found in fish scale incremental patterns, such as those found in coral, otoliths, shells, and bones, is demonstrated. In our previous work, we introduced an empirical model (EM) of arbitrary binary images and three morphological characteristics: disorder of layer structure (DStr), disorder of layer size (DSize), and pattern complexity (PCom). The basic concept of the EM is that forms of lines play no role as a morphological factor in any narrow area of an arbitrary binary image instead, the basic factor is the type of line connectivity, i.e., isotropic/anisotropic connections. The goal of the present work is to justify the possibility of making the EM applicable for the processing of grayscale arbitrary images. One of the possible ways to reach this goal is to assess the influence of image binarization on the robustness of DStr and DSize. Images that exhibit high and low edge gradient are used for this experimental study. The robustness of DStr and DSize against the binarization procedure is described in absolute (deviation from average) and relative (Pearson’s coefficient correlation) terms.
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