Abstract is: Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example: from a television broadcast). Widely used as a form of data entry from printed paper data records – whether passport documents, invoices, bank statements, computerized receipts, business cards, mail, printouts of static-data, or any suitable documentation – it is a common method of digitizing printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining. OCR is a field of research in pattern recognition, artificial intelligence and computer vision. Early versions needed to be trained with images of each character, and worked on one font at a time. Advanced systems capable of producing a high degree of recognition accuracy for most fonts are now common, and with support for a variety of digital image file format inputs. Some systems are capable of reproducing formatted output that closely approximates the original page including images, columns, and other non-textual components.
| document digitization | Q60823508 |
| software feature | Q4485156 |
| algorithm | Q8366 |
| pattern recognition | Q378859 |
| text digitization | Q16946945 |
| data recognition | Q123783455 |
| P1889 | different from | optical music recognition | Q1243229 |
| handwriting recognition | Q2440634 | ||
| P1269 | facet of | scanning | Q11873863 |
| Create or Receive (Acquire) | Q90887043 | ||
| P1813 | short name | OCR | |
| P2579 | studied in | natural language processing | Q30642 |
| P910 | topic's main category | Category:Optical character recognition | Q7436003 |
| P1424 | topic's main template | Template:OCR | Q11000063 |
| P2283 | uses | optical font | Q59154904 |
| Q124348226 | ALTO-XML |
| Q20707736 | Asprise OCR |
| Q124348079 | Calamari |
| Q4226201 | Code stamp |
| Q1143931 | CuneiForm |
| Q24883484 | E-aksharayan |
| Q111395419 | FineReader OCR |
| Q1416880 | FineReader PDF |
| Q2013782 | GNU Ocrad |
| Q1486281 | GOCR |
| Q126000626 | OCR software |
| Q682579 | OCR-A font |
| Q651105 | OCR-B |
| Q124347709 | OCR4all |
| Q4045573 | OCRFeeder |
| Q110575428 | OCRmyPDF |
| Q607628 | OCRopus |
| Q3227436 | OmniPage |
| Q108837791 | OmniPage Pro 12 |
| Q109040714 | PAGE-XML |
| Q61727092 | PrimeOCR |
| Q7259760 | Puma.NET |
| Q110680666 | Readiris |
| Q945242 | Tesseract |
| Q126084619 | Tesseract OCR |
| Q22937321 | Transkribus |
| Q111218645 | eScriptorium |
| Q288405 | hOCR |
| Q97126903 | kraken |
| Q92253197 | optical character reader |
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| Q106947805 | gImageReader |
| Q682579 | OCR-A font | named after | P138 |
| Q11000063 | Template:OCR | template has topic | P1423 |
| Q30642 | natural language processing | is the study of | P2578 |
| Q7436003 | Category:Optical character recognition | category's main topic | P301 |
| Q5287629 | Document Layout Analysis | part of | P361 |
| uri / http://www.wikidata.org/entity/L455849-S1 | L455849-S1 | item for this sense | P5137 |
| Q98591834 | Category:OCR typefaces | category combines topics | P971 |
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