ocrpara

ocrpara is an open-source software toolkit designed to improve the readability and searchability of OCR output by automatically detecting and reconstructing paragraph boundaries in digitized documents. It processes OCR results produced by engines such as Tesseract or OCRopus and can accept input in hOCR, ALTO, or plain text formats. The aim is to restore document structure, particularly in multi-column layouts, documents with irregular line breaks, or archival material.

Key features include paragraph segmentation using language-agnostic heuristics enhanced by machine learning models, support for multiple layouts (single-column, multi-column, tables), language detection, handling of indentation and line spacing cues, and output in structured formats suitable for downstream indexing, display, or further processing. It is designed to be adaptable to different scripts and writing styles and can be used as a library or as a standalone command-line tool.

The architecture is a modular pipeline with input adapters, a layout analysis component, a paragraph segmentation model, and an output generator. It emphasizes interoperability with existing OCR pipelines and can be integrated into larger document processing workflows. The project typically offers both API access and a command-line interface to facilitate scripting and batch operations.

Applications include digitization projects for libraries and archives, academic publishing, and government or legal document processing where preserving paragraph structure improves readability and searchability. Limitations arise from OCR quality and document complexity; highly noisy outputs, unusual layouts, or scripts with non-standard paragraph cues can reduce accuracy. The project is maintained under an open-source license and is hosted on a public version-control platform with community guidelines for contributions.

See also: Optical character recognition, hOCR, ALTO, document layout analysis, paragraph detection.