Optical Character Recognition (OCR)

The video tutorial explains Optical Character Recognition (OCR), a technology used to extract text from images, PDFs, and other digitized formats. It highlights OCR's ability to recognize both printed and handwritten text with high accuracy, often exceeding 99% in high-quality images. The tutorial provides examples of OCR in action, demonstrating its effectiveness in various scenarios. It also discusses numerous applications, such as digitizing notes, processing checks, and validating invoices. The video concludes with exam preparation tips, emphasizing understanding OCR's applications.

What is the primary function of Optical Character Recognition (OCR)?

• To translate languages

• To enhance image quality

• To extract text from digitized formats

• To convert text to speech

How does OCR perform when extracting text from handwritten sources?

• It struggles with accuracy

• It only works with printed text

• It performs well with high accuracy

• It cannot process handwritten text

What level of accuracy does OCR technology typically achieve with typed characters in high-quality images?

• Around 75%

• Less than 50%

• Higher than 99%

• Exactly 90%

Which of the following is NOT a use case for OCR technology?

• Processing official documents

• Digitizing handwritten notes

• Automating bank check deposits

• Enhancing video quality

What is a potential exam question related to OCR applications?

• How to improve OCR accuracy?

• Is processing invoices an application of OCR?

• What is the history of OCR?

• How to design an OCR system?