The characterization of the two-dimensional (2D) leaf
sheath of
the coconut palm
Cocos nucifera
from
digital images is part of a research project that focuses on the feasibility
of using a local natural resource, the leaf sheath of the coconut
palm
C. nucifera
(2D), for the development
of a green composite material and the analysis of the influence of
this type of reinforcement, which has the advantage of being naturally
woven, on the properties of the biocomposites obtained. In order to
characterize these properties, it is essential to extract information
from the leaf sheath samples. This work consists of counting and evaluating
the thicknesses and directions of all the fibers that make up the
sheath. In simple cases, from sample photographs, we wish to propose
a processing chain capable of automating this extraction process.
We are interested here only in samples with areas of spacing between
the fibers. Therefore, our proposal cannot be a solution for tightly
packed fibers. The data are represented by photographs of leaf sheath
samples taken with a high-resolution microscope. This results in color
images of 3000 × 3000 pixels. In the following, we will call
EI a space in which it is possible to locate a pixel by its spatial
coordinates, and we will call EC another space in which it is possible
to locate the color of a pixel by its colorimetric coordinates. In
EI, the set representing the pixels denoting the fiber will be denoted
EF and that representing the void areas will be denoted EV. From these
starting sets, the work consisted of finding a process that allows
the extraction and characterization of points of interest representing
the leaf sheath.