Аннотация
The paper discusses technologies for optimizing software performance. Optimization methods are divided into high-level and low-level, as well as parallelization. An algorithm for classifying and linking fields in a recognized image of an administrative document is described. The features of the implementation of classification and linking tasks are listed, consisting of the use of constellations of text feature points and the modified Levenshtein distance. SDK Smart Document Engine and OCR Tesseract were used. Several ways are described to optimize the performance of the functions for classifying and linking document content. Optimization of the performance of the system for sorting a stream of images of administrative documents is also described. The proposed methods for optimizing software performance are suitable not only for implementing image processing algorithms but also for computational algorithms in which cyclic information processing is carried out. The method can be applied in modern CAD systems to analyze the content of recognized textual files.