Optical character recognition
Optical character recognition
Optical Character Recognition means a technique of digitalizing a handwritten or printed text. Optical Character Recognition (OCR) is a significant sphere of research in computer vision, pattern recognition, and artificial intelligence. OCR is one of the oldest subfields of AI and is now a more advanced technology.
The Role of Optical Character Recognition
How does OCR really work today? It electronically figures out text in a virtual input, scanned document for example, and converts it into readable text via machine for data processing. In short, OCR delivers a searchable form out of physical documents or image files. Google’s image search function, extraction tools, and PDF to .txt converters are some examples of OCR for Azure Computer Vision.
Optical character recognition
Optical Character Recognition means a technique of digitalizing a handwritten or printed text. Optical Character Recognition (OCR) is a significant sphere of research in computer vision, pattern recognition, and artificial intelligence. OCR is one of the oldest subfields of AI and is now a more advanced technology.
The Role of Optical Character Recognition
How does OCR really work today? It electronically figures out text in a virtual input, scanned document for example, and converts it into readable text via machine for data processing. In short, OCR delivers a searchable form out of physical documents or image files. Google’s image search function, extraction tools, and PDF to .txt converters are some examples of OCR for Azure Computer Vision.
How does Optical Character Recognition function?
Despite the simple concept of OCR, the implementation is comparatively tough due tonumerous factors. It can be more complex when instead of typed writing, a non-digital handwriting format is used. The whole process of OCR involves a certain course of steps, which we shall go through here.
1. Document Scanning
This basic step of OCR here connects to a scanner and that decreases the number of variables. Furthermore, the efficiency of this process is enhanced by this step.
2. Imagine Refining
The elements that need to be captured in a document are improved in this step. OCR recognition software improves this step by pixels and edges are refined to get clear and plain text.
3. Binarization
A bi-level document image is produced in this step, containing only white and black colors or areas. The goal of this step is to apply segmentation to separate the foreground and background texts.
4. Character Recognition
Letters or digits are identified by further processing black areas in this step. OCR recognizes these characters with two algorithms: Pattern Recognition and Feature Detection.
5. Accuracy Verification
The recognition results are referenced by using the interior dictionaries by an OCR process to guarantee accuracy.
OCR goes hand in hand with AI Australia and therefore is a key player in the process of computer vision today and in the times to come.