IMAGE SEGMENTATION BY SPIDER MONKEY ALGORITHM FOR AUTOMATED REVERSE DEVELOPMENT OF PRINTED CIRCUIT BOARDS
Abstract
This article analyzes the current state of the problem of printed circuit boards reverse development
in the context of the development of modern society, science and technology. The relationship
between reverse engineering and the global development trend is seen in the context of
Industry 4.0 or the fourth scientific and technological revolution. A review of existing modern
segmentation algorithms based on clustering algorithms is carried out. Their advantages and disadvantages
are revealed. The aim of the article is to automate the process of reverse development
of printed circuit boards. The objective of the article is the development of a new image segmentation
algorithm for its use in an automated system for reverse development of printed circuit
boards. The article presents the theoretical development of the fuzzy algorithm of spider monkey
image segmentation based on the fuzzy c-means algorithm. The principle of operation is to use the
algorithm of arachnid monkeys used to find the maximum distribution of the probability of finding
a similar pixel in the segmented image, then the maxima are assigned by the centers of the segments
and the fuzzy s-means segmentation algorithm is used. The advantage of this developed
algorithm is the automatic determination of the number of clusters and their centers. The theoretical
advantage of this approach is the use of a universal optimization algorithm, which surpasses
analogues in many optimization optimization problems. The algorithm of actions, an automated
system for reverse development of printed circuit boards. The article provides conclusions about
the prospects of research in this direction and suggests the possibility of using the results of the
work. The novelty is the automation of the process of reverse development of printed circuit
boards. The fundamental difference is the use of a new method of segmentation, based on algorithms
of fuzzy c-medium segmentation and spider monkey algorithm.
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