What is OCR
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Introduction to OCR Text Recognition
1. What is OCR
OCR (Optical Character Recognition) refers to an electronic device (such as a scanner or digital camera) that examines characters printed on paper, determines their shape by detecting dark and light patterns, and then uses character recognition methods to translate the shape into a computer The process of text; that is, for printed characters, the text in the paper document is optically converted into a black and white dot matrix image file, and the text in the image is converted into a text format by the recognition software for the word processing software.
How to debug or use auxiliary information to improve the recognition accuracy is the most important topic of OCR, and the term ICR (Intelligent Character Recognition) is also born. The main indicators to measure the performance of an OCR system are rejection rate, false recognition rate, recognition speed, user interface friendliness, product stability, ease of use and feasibility, etc.
2. Development status of OCR technology
In some simple environments, the accuracy of OCR is relatively high (such as electronic documents), but in some complex environments, no one dares to say that they can do well in character recognition today. Now everyone rarely pays attention to how to further improve the accuracy of text recognition in electronic documents, because they focus on more challenging areas.
The traditional OCR method is not enough to deal with text recognition in complex graphics and text scenes. More and more people are focusing on how to read the text in complex scenes and read it accurately as a research topic. In academic terms, it is Scene text recognition (text detection + text recognition).
3. Application fields and value of OCR text recognition technology
-Document recognition, license plate recognition
-Convert PDF documents to Word
-Photo recognition, screenshot recognition, network image recognition
-Paperless office, manuscript editing, and proofreading
-Public opinion monitoring
-Literature search, etc.
4. OCR text recognition classification
OCR text recognition can be mainly divided into printed text recognition and handwritten text recognition.
5. General process of text recognition
At present, there are various methods of OCR text recognition technology, and each recognition process is also different. Here is a brief introduction to the general process of the text recognition method.
-Identify the text area (through the sliding window algorithm, traverse the entire picture, supervised mark the training sample features for judgment, find the target picture, and extract it by the rectangle)
-Divide the text area into different characters (make a one-dimensional sliding window movement in the rectangle, judge the spacing between characters, and divide the characters)
-Character classification (characters are predicted according to the supervised algorithm for the divided characters)
-Text is recognized (eventually the entire character is recognized)
-Post-processing, recognition, and correction, to perform subsequent processing and correction on the recognized text. For example, consider the word Because, the recognition model we designed recognizes it as 8ecause, then we can use the grammar detector to correct this spelling error, replace the 8 with B and complete the recognition correction. In this way, the entire OCR process is over.
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