  The problems of estimating the similarity index of inhomogeneous scientific
publications containing equations and formulas are discussed for the first
time. It is shown that the presence of equations and formulas (as well as
figures, drawings, and tables) is a complicating factor that significantly
complicates the study of such texts. It has been proved that the method for
determining the similarity index of publications, based on taking into account
individual mathematical symbols and parts of equations and formulas, is
ineffective and can lead to erroneous and even completely absurd conclusions.
Possibilities of the most popular software systems Antiplagiat and iThenticate,
currently used in scientific journals, are investigated for detecting
plagiarism and self-plagiarism. The results of processing by the iThenticate
system of specific examples and specific test problems containing equations and
formulas are presented. It has been established that this software system, when
analyzing heterogeneous texts, is often unable to distinguish self-plagiarism
from pseudo-self-plagiarism, seeming real (but false and imaginary)
self-plagiarism. A model complex situation is considered, in which the
identification of self-plagiarism requires the involvement of highly qualified
specialists of a narrow profile. Various ways to improve the work of software
systems for comparing inhomogeneous texts are proposed. This article will be
useful to researchers and university teachers in physics, mathematics, and
engineering, programmers dealing with problems in image recognition and
research topics of digital image processing, as well as a wide range of readers
who are interested in issues of plagiarism and self-plagiarism.
