Abstract: Within the framework of a method of the information
theory it is offered statistics and probabilistic model for definition of
cause-and-effect relations in the coupled multicomponent
subsystems. The quantitative parameter which is defined through
conditional and unconditional entropy functions is introduced. The
method is applied to the analysis of the experimental data on
dynamics of change of the chemical elements composition of plants
organs (roots, reproductive organs, leafs and stems). Experiment is
directed on studying of temporal processes of primary soil formation
and their connection with redistribution dynamics of chemical
elements in plant organs. This statistics and probabilistic model
allows also quantitatively and unambiguously to specify the
directions of the information streams on plant organs.
Abstract: In this work a novel approach for color image
segmentation using higher order entropy as a textural feature for
determination of thresholds over a two dimensional image histogram
is discussed. A similar approach is applied to achieve multi-level
thresholding in both grayscale and color images. The paper discusses
two methods of color image segmentation using RGB space as the
standard processing space. The threshold for segmentation is decided
by the maximization of conditional entropy in the two dimensional
histogram of the color image separated into three grayscale images of
R, G and B. The features are first developed independently for the
three ( R, G, B ) spaces, and combined to get different color
component segmentation. By considering local maxima instead of the
maximum of conditional entropy yields multiple thresholds for the
same image which forms the basis for multilevel thresholding.