Statistical Characteristics of Optical Signals and Images in Machine Vision Systems

Abstract

The chapter is devoted to the creation of a comprehensive approach to the physical and mathematical description of signals in optoelectronics in machine vision, taking into account the phenomena of interaction of optical radiation with system elements. A new methodology for the study of the statistical properties of input and output signals in optoelectronic systems is proposed, taking into account the availability of grouped statistical properties that do not obey the Poisson statistics. The basis is the joint use of wave and corpuscular description of signals in systems, stochastic flow theories, and elements of statistical detection theory. Information and energetic technology have been developed that integrates the theoretical justification of signal description under various observation conditions and decision-making methods.

Hydrogen Cooling of Turbo Aggregates and the Problem of Rotor Shafts Materials Degradation Evaluation

“…Machine and computer vision is an important technology in Industry 4.0, as it enables the automation of quality control and defect detection in manufacturing. Machine vision systems use cameras and image processing algorithms to capture and analyze images of products in real time to detect defects or anomalies that are difficult to detect with the naked eye [153][154][155][156].…”