{"id":102437,"date":"2021-12-01T15:37:06","date_gmt":"2021-12-01T13:37:06","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/reliz-sistemy-raspoznavaniya-teksta-tesseract-5-0"},"modified":"2021-12-01T15:37:06","modified_gmt":"2021-12-01T13:37:06","slug":"reliz-sistemy-raspoznavaniya-teksta-tesseract-5-0","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/reliz-sistemy-raspoznavaniya-teksta-tesseract-5-0","title":{"rendered":"Release of the Tesseract 5.0 text recognition system.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

The release of the optical character recognition system Tesseract 4.1 has been published, supporting UTF-8 character recognition and text in over 100 languages, including Russian, Kazakh, Belarusian, and Ukrainian. The results can be saved as plain text or in HTML formats (hOCR), ALTO (XML), PDF, and TSV. The system was originally created in 1985-1995 in the laboratory of Hewlett Packard, and in 2005, the code was released under the Apache license and further developed with the participation of Google employees. The project's source texts are distributed under the Apache 2.0 license. <\/p>\n

Tesseract includes a console utility and the libtesseract library for embedding text recognition features in other applications. Among the third-party GUI interfaces supporting Tesseract are gImageReader, VietOCR, and YAGF. It offers two recognition engines: a classic one that recognizes text at the character template level, and a new one based on a recurrent neural network (RNN) machine learning system optimized for recognizing entire lines, allowing for a significant increase in accuracy. Pre-trained models are published for 123 languages. Performance optimization modules use OpenMP and SIMD instructions AVX2, AVX, NEON, or SSE4.1. <\/p>\n

The main improvements in Tesseract 5.0: <\/p>\n