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This research addresses topical issues of creating industrial monitoring systems for chips, which are formed when materials are cut, based on light field-based optical detectors. A proposed scheme uses a light field (LF) method to register formed chips with an optical detector. An algorithms and monitoring methods for key geometric parameters of chip shapes are developed based on the analysis of images obtained from LF cameras. They feature digital image capturing and morphological analysis. For practical implementation of developed algorithms, National Instruments software platform is used. This research shows that the result accuracy in determining geometric characteristics of chips using the proposed solutions makes it possible to run diagnostics for cutting and material processing equipment.

The data about the effect of image quality on accuracy of information parameters are presented. Studies on accuracy of measuring characteristics of objects in their images depending on image quality are described. Studies showed that accuracy of measurement algorithms improves with an increase in sample sizes of frames in the optoelectronic system (OES). Image quality is improved by processing the frame samples with algorithms for increasing resolution and reducing noise levels, both in single-point and multi-position OESs based on digital cameras with matrix photodetectors. The maximum effect of an increase in information content of the image and accuracy of measuring algorithms is determined by variations in the pixel structure of each image in the region of brightness gradient boundaries. In the single-point OESs which ensure high quality of optical images without noise factors and variations of other external parameters, the optimal number of frames in the OES is four.

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