Optical Character Recognition in the Real World
To understand how OCR works, consider a printed document with names, addresses, and other useful information like courses taken and grades received. To manipulate this data and find out specific information, the information needs to be in a format that can be accessed on a PC.
Through the use of OCR, images are processed in a variety of different ways to boost opportunities for character recognition. These techniques include:
- De-skewing – documents scanned are not always correctly aligned. The software is able to correct for this discrepancy by adjusting the image.
- Despeckle – OCR software can remove positive and negative spots from images and also smooth the edges to make the text more recognizable.
- Binarization – by converting images into black-and-white, text is more easily discovered.
- Line removal and layout analysis – OCR software is able to identify columns, lines, and paragraphs as blocks. This helps to ensure text can be manipulated more easily.
- Script and word recognition – with documents that have multiple languages present, the software needs to understand the differences and correctly analyze and divide words.
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Optical Character Recognition in the World of AI
OCR is being revolutionized through the use of AI. Now, data is not only captured and analyzed, but based on the information obtained, appropriate action is taken. Some examples of the combination of OCR and AI include a streamlining of the invoicing process for organizations based on scanned data. In a similar vein, OCR and AI can be used to verify expense management by ensuring related entries are automatically flagged.