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By Joaquim Rocha. ...
By Joaquim Rocha.
Even with all the existing alternatives, nowadays a lot of information is still printed on paper. From historical documents to places that only recently started to use digital documents in their usual workflow, this information is conditioned by the limitations of paper: hard to index and search, risk of deterioration, ecological implications, etc.
Fortunately the state of the art Optical Character Recognition engines, including Free Software solutions, have high success rates in converting printed text into a digital format. However, these command-line tools only convert graphics in text, usually not taking into consideration the layout of the documents analyzed. This means that a regular page with a mixture of text in columns and eventual graphics will be read as if it was only text. There are some solutions that do take into account the structure of the documents besides performing OCR but these are proprietary and commercial and usually do not a version for Linux.
OCRFeeder attempts to solve this problem. It automatically tries to outline the structure of the document (using its own algorithm), detect between graphics and text and performs OCR. Its main exportation format is ODT but it can also export to HTML and save or load projects. It is also possible to use different system-wide OCR engines in the same document and manually override any automatic action (for example, to correct its results, etc.). OCRFeeder is published under GPL v3 and was thought to be used mainly in the GNOME desktop environment and it's developed in its infrastructure. It stands as the only Free Software solution to provide a complete and easy to use graphical user interface application to convert printed documents.
When used with the Orca screen reader, OCRFeeder is also a useful application for the visually impaired since it enables a printed document to be converted and read by Orca. Thus, during 2010, the main focus of OCRFeeder's development was the improvement of its accessibility
Currently, the main features of OCRFeeder are:
- Detection of the contents in a document's page;
- Classification of those contents (graphics or text);
- Deskew of images;
- Importation from a scanner device or PDF;
- Exportation to ODT or HTML;
- Manual edition of any results.
- Save and load projects.
In this presentation I will explain how OCRFeeder's contents detection algorithm works, how a usual workflow to convert a document should be and give an overview of the main features of OCRFeeder with a demo.