Tesseract OCR Engine

Tesseract is an open-source optical character recognition (OCR) engine, widely regarded as one of the most accurate OCR engines available. Originally developed at Hewlett-Packard Laboratories by Ray Smith between 1984 and 1994, later open-sourced by HP and UNLV in 2005, and significantly enhanced by Google from 2006 to 2018, Tesseract has over 62,000 stars as of 2026 and supports over 100 languages. Key features include: multi-language support (over 100 languages with trained data files, including Chinese, Japanese, Korean, Arabic, and right-to-left scripts, with the ability to load multiple languages simultaneously), LSTM neural network (deep learning-based recognition engine introduced in Tesseract 4, providing significantly improved accuracy over the legacy Tesseract engine for complex scripts and degraded text), text recognition modes (page segmentation mode for automatic layout analysis, single line, single word, single character, sparse text, and vertical text modes), output formats (plain text, hOCR, TSV, ALTO XML, PDF with searchable text overlay, and BOX files for training data creation), image preprocessing (integration with Leptonica for image binarization, deskewing, and page layout analysis), training tools (creating custom trained data for new languages, fonts, and specialized document types), API bindings (C++, Python via pytesseract, Java via Tess4J, Go, Ruby, Node.js, and command-line interface), page layout analysis (detecting text blocks, paragraphs, lines, words, and reading order for complex documents), confidence scoring (per-word and per-symbol confidence values for quality assessment), and DPI-aware scaling (adaptive recognition based on input image resolution).