The article provides an overview of the analysis and diagnosis of product surface defects, evaluated using digital image processing. The search for scientific publications was carried out mainly in the Scopus and RSCI scientometric bases for the period 2019-2023. The purpose of this article is to determine the best methods for assessing the destruction of materials using digital images. The main methods of processing and analyzing digital images are considered. The perspective of unification of segmentation modes by digital image acquisition sources and combining images from various recording sources to obtain objective information on the nature of material destruction is shown. To reduce the time for assessing the degree of destruction of materials, it is proposed to gradually use the methods of segmentation, filtering digital images of defects in metal products with subsequent calculation by a neural network.

Keywords: defect, control, digital image, neural network.

Annotation: The possibility of quality assessing of paint coatings by using the products surface conditions analysis through the use of digital technologies is shown. In the conditions of industrial enterprise, the comparative analysis of АК-1301 and Tikkurila Metallista coatings condition, exposed to aggressive environments: water, gasoline is carried out. From digital images of the surface, adhesive strength and the porosity of the coatings before-and-after the effects of the environments were assessed. It is shown that АК-1301 enamel has the highest adhesive strength and chemical resistance to water and gasoline.

Keywords: paint coating, adhesion, surface porosity, corrosive environment, digital image, pixel