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Showing posts with the label tesseract-OCR

2021-12-31: Installing Several Open Source and Commercial Optical Character Recognition (OCR) Tools on a PC

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  Optical Character Recognition (OCR) tools are used for extracting text from images. There are many off-the-shelf OCR tools we can choose from. In a previous blogpost , I compared the performance of several open-source and commercial OCR tools. I’d like to go further and summarize the installation of these tools. In this blogpost, I will talk about the installation of Tesseract, Abbyy, Amazon Textract, and Google Cloud Vision. Tesseract: Tesseract is a free software package which accepts a wide range of file formats such as JEPG, PNG, TIFF, and BMP. The installation on a Win10 system is as follows: Step 1:  Download tesseract executable file  tesseract.exe  from this website .  Double click the file and it will guide you through installation. Step 2: Download the language package to the installation directory of the tesseract executable file. It must be compatible with the version of tesseract.exe . This is the ...

2021-09-19: Conditional Random Field with Textual and Visual Features to Extract Metadata From Scanned ETDs

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Our previous  blog  described Electronic Theses and Dissertations (ETDs) before 1997, and a significant fraction of ETDs after 1997 are scanned from physical copies. These ETDs are valuable for digital library preservation, but to make them accessible, it is necessary to index these ETDs. Many ETD repositories are accompanied by incomplete, little, or no metadata, posing challenges for accessibility. For example, advisor names appearing on the Scanned ETDs may not be available in the metadata provided in the library repository. Thus, an automatic approach should be adopted to extract metadata from scanned ETDs. We proposed a conditional random field (CRF) based sequence tagging model that combines textual and visual features . The source code can be found in our GitHub repository. Introduction Automatic metadata extraction is important to build scalable digital library search engines. Most existing tools such as GROBID [1], CERMINE [2], and ParsCit [3] developed and applied t...

2020-05-19: OCR Tools Experiment on Scanned Electronic Theses and Dissertations (ETDs)

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A thesis or dissertation is one type of scholarly work that shows a student pursuing higher education and has successfully met the partial requirement of a degree. An electronic thesis or dissertation can be found from either a university's electronic theses and dissertations (ETDs) digital library or ProQuest (a third party ETD repository). ETDs contain lots of rich metadata that can be used for searching ETDs from the repository. However, not all ETD metadata are available. Therefore, it is necessary to extract metadata from scholarly ETDs. Also, extracting metadata could be challenging, mainly when it is found as scanned academic ETDs. Although many open-source tools exhibit satisfying performance in certain types of documents, experiments indicate that they tend to produce unacceptable errors or fail on scanned ETDs. In this blog post, I introduce one of the widely used optical character recognition (OCR) tools called tesseract-OCR and show how tesseract-OCR performs on scann...