Abstract:
Image processing systems are currently used to solve many applied
problems. The article is devoted to the identification of negative factors
affecting the growth of grain in different periods of harvesting, using a
program implemented in the MATLAB software environment, based on
aerial photographs. The program is based on the Law’s textural mask
method and successive clustering. This paper presents the algorithm of the
program and shows the results of image processing by highlighting the
uniformity of the image. To solve the problem, the spectral luminance
coefficient (SBC), normalized difference vegetation index (NDVI), Law’s
textural mask method, and clustering are used. This approach is general and
has great potential for identifying objects and territories with different
boundary properties on controlled aerial photographs using groups of images
of the same surface taken at different vegetation periods. That is, the
applicability of sets of Laws texture masks with original image enhancement
for the analysis of experimental data on the identification of pest outbreaks
is being investigated.
